Merge remote-tracking branch 'origin/push-dev' into push-dev-preprocess

algorithm/src/main/resources/algorithm.properties

@@ -1,6 +1,6 @@
 ################################ model basic url ###################################
 
-#basicPath=E:/git/push/algorithm/src/main/models/model_version_replacement/model
+#basicPath=E:/project/push/algorithm/src/main/models/model_version_replacement/model
 basicPath=/opt/models/dev/models/model_version_replacement/model
 #basicPath=E:/xxx/model_version_replacement/model
 

bigdata-web/src/main/java/org/diagbot/bigdata/common/ApplicationCacheUtil.java

@@ -22,8 +22,8 @@ public class ApplicationCacheUtil {
     public static Map<String, String> standard_info_classify_map = null;
     //树形结构存储大小类
     public static Map<String, NlpCache.Node> standard_info_type_tree_map = null;
-    //体征衍射
-    public static Map<String, String> doc_result_mapping_vital_map = null;
+//    体征衍射
+//    public static Map<String, String> doc_result_mapping_vital_map = null;
     //诊断科室衍射
     public static Map<String, String> doc_result_mapping_diag_map = null;
     //特征性别 年龄过滤等
@@ -52,141 +52,164 @@ public class ApplicationCacheUtil {
         return standard_info_type_tree_map;
     }
 
-    public static Map<String, String> getDoc_result_mapping_vital_map() {
-        if (doc_result_mapping_vital_map == null) {
-            Configuration configuration = new DefaultConfig();
-            doc_result_mapping_vital_map = configuration.loadMapDict("doc_result_mapping_vital.dict");
-        }
-        return doc_result_mapping_vital_map;
-    }
+//    /**
+//     * 現已無用
+//     * @return
+//     */
+//    public static Map<String, String> getDoc_result_mapping_vital_map() {
+//        if (doc_result_mapping_vital_map == null) {
+//            Configuration configuration = new DefaultConfig();
+//            doc_result_mapping_vital_map = configuration.loadMapDict("doc_result_mapping_vital.dict");
+//        }
+//        return doc_result_mapping_vital_map;
+//    }
 
     public static Map<String, String> getDoc_result_mapping_diag_map() {
         if (doc_result_mapping_diag_map == null) {
-            Configuration configuration = new DefaultConfig();
-            doc_result_mapping_diag_map = configuration.loadMapDict("doc_result_mapping_diag.dict");
+            createDoc_result_mapping_diag_map();
         }
         return doc_result_mapping_diag_map;
     }
 
-    public static Map<String, Map<String, ResultMappingFilter>> getDoc_result_mapping_filter_map() {
+    public static Map<String, String> createDoc_result_mapping_diag_map() {
         Configuration configuration = new DefaultConfig();
+        doc_result_mapping_diag_map = configuration.loadMapDict("bigdata_diag_2_dept.dict");
+        return doc_result_mapping_diag_map;
+    }
+
+    public static Map<String, Map<String, ResultMappingFilter>> getDoc_result_mapping_filter_map() {
         if (doc_result_mapping_filter_map == null) {
-            List<String> fileContents = configuration.readFileContents("doc_result_mapping_filter.dict");
-            String[] line_string;
-            List<ResultMappingFilter> resultMappingFilters = new ArrayList<>();
-            try {
-                for (int i = 0; i < fileContents.size(); i++) {
-                    line_string = org.apache.commons.lang3.StringUtils.split(fileContents.get(i), "\\|");
-                    if (line_string.length == 5) {
-                        ResultMappingFilter resultMappingFilter = new ResultMappingFilter();
-                        resultMappingFilter.setFeatureName(line_string[0]);
-                        resultMappingFilter.setFeatureType(line_string[1]);
-                        resultMappingFilter.setSex(line_string[2]);
-                        resultMappingFilter.setAgeStart(Integer.parseInt(line_string[3]));
-                        resultMappingFilter.setAgeEnd(Integer.parseInt(line_string[4]));
-                        resultMappingFilters.add(resultMappingFilter);
-                    }
+            createDoc_result_mapping_filter_map();
+        }
+        return doc_result_mapping_filter_map;
+    }
+
+    public static Map<String, Map<String, ResultMappingFilter>> createDoc_result_mapping_filter_map() {
+        Configuration configuration = new DefaultConfig();
+        List<String> fileContents = configuration.readFileContents("bigdata_sex_age_filter.dict");
+        String[] line_string;
+        List<ResultMappingFilter> resultMappingFilters = new ArrayList<>();
+        try {
+            for (int i = 0; i < fileContents.size(); i++) {
+                line_string = org.apache.commons.lang3.StringUtils.split(fileContents.get(i), "\\|");
+                if (line_string.length == 5) {
+                    ResultMappingFilter resultMappingFilter = new ResultMappingFilter();
+                    resultMappingFilter.setFeatureName(line_string[0]);
+                    resultMappingFilter.setFeatureType(line_string[1]);
+                    resultMappingFilter.setSex(line_string[2]);
+                    resultMappingFilter.setAgeStart(Integer.parseInt(line_string[3]));
+                    resultMappingFilter.setAgeEnd(Integer.parseInt(line_string[4]));
+                    resultMappingFilters.add(resultMappingFilter);
                 }
-            } catch (Exception e) {
-                e.printStackTrace();
             }
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
 
-            doc_result_mapping_filter_map = new HashMap<>();
-            Map<String, ResultMappingFilter> filterMap = null;
-            for (ResultMappingFilter resultMappingFilter : resultMappingFilters) {
-                filterMap = doc_result_mapping_filter_map.get(resultMappingFilter.getFeatureType());
-                if (filterMap == null) {
-                    filterMap = new HashMap<>();
-                }
-                filterMap.put(resultMappingFilter.getFeatureName(), resultMappingFilter);
-                doc_result_mapping_filter_map.put(resultMappingFilter.getFeatureType(), filterMap);
+        doc_result_mapping_filter_map = new HashMap<>();
+        Map<String, ResultMappingFilter> filterMap = null;
+        for (ResultMappingFilter resultMappingFilter : resultMappingFilters) {
+            filterMap = doc_result_mapping_filter_map.get(resultMappingFilter.getFeatureType());
+            if (filterMap == null) {
+                filterMap = new HashMap<>();
             }
+            filterMap.put(resultMappingFilter.getFeatureName(), resultMappingFilter);
+            doc_result_mapping_filter_map.put(resultMappingFilter.getFeatureType(), filterMap);
         }
         return doc_result_mapping_filter_map;
     }
 
     public static Map<String, List<Map<String, String>>> getKl_result_mapping_standword_map() {
         if (kl_result_mapping_standword_map == null) {
-            kl_result_mapping_standword_map = new HashMap<>();
-            Configuration configuration = new DefaultConfig();
-            List<String> fileContents = configuration.readFileContents("kl_result_mapping_standword.dict");
-            List<Map<String, String>> standWordObjValList = null;
-            Map<String, String> standWordObjVal = null;
-            String operation = ">=|≥|>|大于|＞|超过|<=|≤|<|小于|＜|少于";
-            try {
-                for (String fileContent : fileContents) {
-                    LexemePath<Lexeme> lexemes = null;
-                    String op = "";
-                    String[] fileContentSplit = null;
-                    //每一个标准词根据大于小于符号切开，不然进行分词时还是会得到原本的标准词
-                    if (fileContent.contains(">") || fileContent.contains("大于")
-                            || fileContent.contains("＞") || fileContent.contains("超过")) {
-                        op = ">";
-                        fileContentSplit = fileContent.split(operation);
-                    } else if (fileContent.contains("<") || fileContent.contains("小于")
-                            || fileContent.contains("＜") || fileContent.contains("少于")) {
-                        op = "<";
-                        fileContentSplit = fileContent.split(operation);
-                    } else if (fileContent.contains(">=") || fileContent.contains("≥")){
-                        op = ">=";
-                        fileContentSplit = fileContent.split(operation);
-                    } else if (fileContent.contains("<=") || fileContent.contains("≤")) {
-                        op = "<=";
-                        fileContentSplit = fileContent.split(operation);
-                    } else {
-                        continue;
-                    }
-                    LexemePath<Lexeme> lexemeWord = null;
-                    //每一个标准词切开后进行分词
-                    for (String fileContentWords : fileContentSplit) {
-                        lexemeWord = ParticipleUtil.participle(fileContentWords);
-                        if (lexemeWord != null) {
-                            if (null == lexemes) {
-                                lexemes = lexemeWord;
-                            } else {
-                                for (Lexeme lexeme : lexemeWord) {
-                                    lexemes.add(lexeme);
-                                }
+            createKl_result_mapping_standword_map();
+        }
+        return kl_result_mapping_standword_map;
+    }
+
+    public static Map<String, List<Map<String, String>>> createKl_result_mapping_standword_map() {
+        kl_result_mapping_standword_map = new HashMap<>();
+        Configuration configuration = new DefaultConfig();
+        List<String> fileContents = configuration.readFileContents("bigdata_value_analyze.dict");
+        List<Map<String, String>> standWordObjValList = null;
+        Map<String, String> standWordObjVal = null;
+        String operation = ">=|≥|>|大于|＞|超过|<=|≤|<|小于|＜|少于";
+        try {
+            for (String fileContent : fileContents) {
+                LexemePath<Lexeme> lexemes = null;
+                String op = "";
+                String[] fileContentSplit = null;
+                //每一个标准词根据大于小于符号切开，不然进行分词时还是会得到原本的标准词
+                if (fileContent.contains(">") || fileContent.contains("大于")
+                        || fileContent.contains("＞") || fileContent.contains("超过")) {
+                    op = ">";
+                    fileContentSplit = fileContent.split(operation);
+                } else if (fileContent.contains("<") || fileContent.contains("小于")
+                        || fileContent.contains("＜") || fileContent.contains("少于")) {
+                    op = "<";
+                    fileContentSplit = fileContent.split(operation);
+                } else if (fileContent.contains(">=") || fileContent.contains("≥")){
+                    op = ">=";
+                    fileContentSplit = fileContent.split(operation);
+                } else if (fileContent.contains("<=") || fileContent.contains("≤")) {
+                    op = "<=";
+                    fileContentSplit = fileContent.split(operation);
+                } else {
+                    continue;
+                }
+                LexemePath<Lexeme> lexemeWord = null;
+                //每一个标准词切开后进行分词
+                for (String fileContentWords : fileContentSplit) {
+                    lexemeWord = ParticipleUtil.participle(fileContentWords);
+                    if (lexemeWord != null) {
+                        if (null == lexemes) {
+                            lexemes = lexemeWord;
+                        } else {
+                            for (Lexeme lexeme : lexemeWord) {
+                                lexemes.add(lexeme);
                             }
                         }
                     }
-                    String standWordObjKey = "";
-                    standWordObjValList = new ArrayList<>();
-                    standWordObjVal = new HashMap<>();
-                    int i = 0;
-                    for (Lexeme lexeme : lexemes) {
-                        i++;
-                        if (lexeme.getProperty().contains(",")) {
-                            setProterty(lexeme); //如果分词后词性有多个，只选一个(暂时只处理症状,体征)
-                        }
-                        NegativeEnum lexemeNegativeEnum = NegativeEnum.parseOfValue(lexeme.getProperty());
-                        if (lexemeNegativeEnum == NegativeEnum.SYMPTOM || lexemeNegativeEnum == NegativeEnum.CAUSE
-                                || lexemeNegativeEnum == NegativeEnum.VITAL_INDEX) {
-                            if (!kl_result_mapping_standword_map.containsKey(lexeme.getText())) {
-                                kl_result_mapping_standword_map.put(lexeme.getText(), standWordObjValList);
-                            } else {
-                                standWordObjKey = lexeme.getText();
-                            }
-                        } else if (lexemeNegativeEnum == NegativeEnum.DIGITS) {
-                            standWordObjVal.put("value", lexeme.getText());
-                        } else if (lexemeNegativeEnum == NegativeEnum.UNIT
-                                || lexemeNegativeEnum == NegativeEnum.EVENT_TIME) {
-                            standWordObjVal.put("unit", lexeme.getText().toLowerCase());
+                }
+                String standWordObjKey = "";
+                standWordObjValList = new ArrayList<>();
+                standWordObjVal = new HashMap<>();
+                int i = 0;
+                for (Lexeme lexeme : lexemes) {
+                    i++;
+                    if (lexeme.getProperty().contains(",")) {
+                        setProterty(lexeme); //如果分词后词性有多个，只选一个(暂时只处理症状,体征)
+                    }
+                    NegativeEnum lexemeNegativeEnum = NegativeEnum.parseOfValue(lexeme.getProperty());
+                    if (lexemeNegativeEnum == NegativeEnum.SYMPTOM || lexemeNegativeEnum == NegativeEnum.CAUSE
+                            || lexemeNegativeEnum == NegativeEnum.VITAL_INDEX
+                            || lexemeNegativeEnum == NegativeEnum.DIAG_STAND) {
+                        if (!kl_result_mapping_standword_map.containsKey(lexeme.getText())) {
+                            kl_result_mapping_standword_map.put(lexeme.getText(), standWordObjValList);
+                        } else {
+                            standWordObjKey = lexeme.getText();
                         }
-                        if (lexemes.size() == i) {
-                            standWordObjVal.put("op", op);
-                            standWordObjVal.put("standword", fileContent);
-                            if (kl_result_mapping_standword_map.containsKey(standWordObjKey)) {
-                                kl_result_mapping_standword_map.get(standWordObjKey).add(standWordObjVal);
-                            } else {
-                                standWordObjValList.add(standWordObjVal);
-                            }
+                    }
+                    if (lexemeNegativeEnum == NegativeEnum.DIGITS) {
+                        standWordObjVal.put("value", lexeme.getText());
+                    }
+                    if (lexemeNegativeEnum == NegativeEnum.UNIT
+                            || lexemeNegativeEnum == NegativeEnum.EVENT_TIME
+                            || lexemeNegativeEnum == NegativeEnum.OTHER) {
+                        standWordObjVal.put("unit", lexeme.getText().toLowerCase());
+                    }
+                    if (lexemes.size() == i) {
+                        standWordObjVal.put("op", op);
+                        standWordObjVal.put("standword", fileContent);
+                        if (kl_result_mapping_standword_map.containsKey(standWordObjKey)) {
+                            kl_result_mapping_standword_map.get(standWordObjKey).add(standWordObjVal);
+                        } else {
+                            standWordObjValList.add(standWordObjVal);
                         }
                     }
                 }
-            } catch (Exception e) {
-                e.printStackTrace();
             }
+        } catch (Exception e) {
+            e.printStackTrace();
         }
         return kl_result_mapping_standword_map;
     }
@@ -200,6 +223,10 @@ public class ApplicationCacheUtil {
                 case "33":
                     lexeme.setProperty("33");
                     break;
+                case "70":
+                    lexeme.setProperty("70");
+                    break;
+
             }
         }
     }

bigdata-web/src/main/java/org/diagbot/bigdata/work/ParamsDataProxy.java

@@ -28,6 +28,25 @@ import java.util.regex.Pattern;
  **/
 public class ParamsDataProxy {
     Logger logger = LoggerFactory.getLogger(ParamsDataProxy.class);
+    //标准词只处理的词性
+    public static NegativeEnum[] negativeEnums = new NegativeEnum[] { NegativeEnum.VITAL_INDEX, NegativeEnum.SYMPTOM
+            , NegativeEnum.DIGITS, NegativeEnum.EVENT_TIME, NegativeEnum.UNIT, NegativeEnum.DIAG_STAND
+            , NegativeEnum.OTHER};
+    //标准词处理的三元组
+    public static NegativeEnum[][] negativeEnumTriple = {
+            { NegativeEnum.VITAL_INDEX, NegativeEnum.DIGITS, NegativeEnum.UNIT },
+            { NegativeEnum.VITAL_INDEX, NegativeEnum.DIGITS, NegativeEnum.EVENT_TIME },
+            { NegativeEnum.SYMPTOM, NegativeEnum.DIGITS, NegativeEnum.UNIT },
+            { NegativeEnum.SYMPTOM, NegativeEnum.DIGITS, NegativeEnum.EVENT_TIME },
+            { NegativeEnum.DIAG_STAND, NegativeEnum.DIGITS, NegativeEnum.UNIT },
+            { NegativeEnum.DIAG_STAND, NegativeEnum.DIGITS, NegativeEnum.EVENT_TIME },
+            { NegativeEnum.DIAG_STAND, NegativeEnum.DIGITS, NegativeEnum.OTHER }
+    };
+    //标准词处理的二元组
+    public static NegativeEnum[][] negativeEnumTwoTuple = {
+            { NegativeEnum.VITAL_INDEX, NegativeEnum.DIGITS },
+            { NegativeEnum.SYMPTOM, NegativeEnum.DIGITS }
+    };
 
     public void createSearchData(HttpServletRequest request, SearchData searchData) throws Exception {
         //消除空格
@@ -59,10 +78,15 @@ public class ParamsDataProxy {
             searchData.setResourceType(BigDataConstants.resource_type_o);
         }
         //给症状末尾添加诊断依据标准词
-        if (searchData.getSymptom() != null) {
-            LexemePath<Lexeme> featureData = ParticipleUtil.participle(searchData.getSymptom());
-            if (featureData != null) {
-                addStandWord(featureData, ApplicationCacheUtil.getKl_result_mapping_standword_map(), searchData);
+        String[] items = { searchData.getSymptom(), searchData.getOther(), searchData.getVital()
+                , searchData.getLis(), searchData.getPacs(), searchData.getDiag() };
+        String[] itemsType = { "symptom", "other", "vital", "lis", "pacs", "diag" };
+        for (int i = 0; i < items.length; i++) {
+            if (items[i] != null) {
+                LexemePath<Lexeme> featureData = ParticipleUtil.participle(items[i]);
+                if (featureData != null) {
+                    addStandWord(featureData, ApplicationCacheUtil.getKl_result_mapping_standword_map(), searchData, itemsType[i]);
+                }
             }
         }
         //所有信息参与推送
@@ -104,7 +128,7 @@ public class ParamsDataProxy {
         }
         if (!StringUtils.isEmpty(searchData.getOther()) || !StringUtils.isEmpty(searchData.getIndications())) {
             //提取其他史等
-            featuresList = fa.start(searchData.getOther() == null ? "" : searchData.getOther() + searchData.getIndications() == null ? "" : searchData.getIndications(), FeatureType.FEATURE);
+            featuresList = fa.start((searchData.getOther() == null ? "" : searchData.getOther()) + (searchData.getIndications() == null ? "" : searchData.getIndications()), FeatureType.FEATURE);
             paramFeatureInit(searchData, featuresList);
         }
         if (!StringUtils.isEmpty(searchData.getPacs())) {
@@ -289,73 +313,82 @@ public class ParamsDataProxy {
      * @param sData
      * @return
      */
-    public SearchData addStandWord(List<Lexeme> lexemes, Map<String, List<Map<String, String>>> standWords, SearchData sData) {
+    public SearchData addStandWord(List<Lexeme> lexemes, Map<String, List<Map<String, String>>> standWords, SearchData sData, String itemType) {
         List<Lexeme> feature = new ArrayList<>();
+
         //收集分词结果中体征指标或体征指标值（数字）
         for (Lexeme lexeme : lexemes) {
             if (lexeme.getProperty().contains(",")) {
                 ApplicationCacheUtil.setProterty(lexeme); //如果分词后词性有多个，只选一个(暂时只处理症状,体征)
             }
             NegativeEnum lexemeNegativeEnum = NegativeEnum.parseOfValue(lexeme.getProperty());
-            if (lexemeNegativeEnum == NegativeEnum.VITAL_INDEX || lexemeNegativeEnum == NegativeEnum.SYMPTOM || lexemeNegativeEnum == NegativeEnum.DIGITS
-                    || lexemeNegativeEnum == NegativeEnum.EVENT_TIME || lexemeNegativeEnum == NegativeEnum.UNIT
-                    ) {
-                feature.add(lexeme);
+            for (int i = 0; i < negativeEnums.length; i++) {
+                if (lexemeNegativeEnum == negativeEnums[i]) {
+                    feature.add(lexeme);
+                    break;
+                }
             }
         }
         //根据收集到的分词结果把体征指标和对应体征指标值（数字）拼接
         List<String> featureType = new ArrayList<>();
+
         for (int i = 0; i < feature.size(); i++) {
             boolean featureTypeState = true;
+            boolean featureTypeStatus = false;
             if (i < feature.size() - 2) {
-                if ((NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.VITAL_INDEX
-                        && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS
-                        && NegativeEnum.parseOfValue(feature.get(i + 2).getProperty()) == NegativeEnum.UNIT)
-                        ||
-                        (NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.VITAL_INDEX
-                                && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS
-                                && NegativeEnum.parseOfValue(feature.get(i + 2).getProperty()) == NegativeEnum.EVENT_TIME)
-                        ||
-                        (NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.SYMPTOM
-                                && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS
-                                && NegativeEnum.parseOfValue(feature.get(i + 2).getProperty()) == NegativeEnum.UNIT)
-                        ||
-                        (NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.SYMPTOM
-                                && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS
-                                && NegativeEnum.parseOfValue(feature.get(i + 2).getProperty()) == NegativeEnum.EVENT_TIME)) {
-                    featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText() + "\t"
-                            + feature.get(i + 2).getText());
-                    featureTypeState = false;
+                for (int j = 0; j < negativeEnumTriple.length; j++) {
+                    String featureText = "";
+                    for (int k = 0; k < negativeEnumTriple[j].length; k++) {
+                        if (NegativeEnum.parseOfValue(feature.get(i + k).getProperty()) == negativeEnumTriple[j][k]) {
+                            featureTypeStatus = true;
+                            featureText += "\t" + feature.get(i + k).getText();
+                        } else {
+                            featureTypeStatus = false;
+                            break;
+                        }
+                    }
+                    if (featureTypeStatus) {
+                        featureType.add(featureText);
+                        featureTypeState = false;
+                    }
                 }
             }
             if (featureTypeState && i < feature.size() - 1) {
-                if ((NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.VITAL_INDEX
-                        && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS)
-                        ||
-                        (NegativeEnum.parseOfValue(feature.get(i).getProperty()) == NegativeEnum.SYMPTOM
-                                && NegativeEnum.parseOfValue(feature.get(i + 1).getProperty()) == NegativeEnum.DIGITS)) {
-                    featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText());
+                for (int j = 0; j < negativeEnumTwoTuple.length; j++) {
+                    String featureText = "";
+                    for (int k = 0; k < negativeEnumTwoTuple[j].length; k++) {
+                        if (NegativeEnum.parseOfValue(feature.get(i + k).getProperty()) == negativeEnumTwoTuple[j][k]) {
+                            featureTypeStatus = true;
+                            featureText += "\t" + feature.get(i + k).getText();
+                        } else {
+                            featureTypeStatus = false;
+                            break;
+                        }
+                    }
+                    if (featureTypeStatus) {
+                        featureType.add(featureText);
+                    }
                 }
             }
         }
         //将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
         String newStandWord = "";
         for (String f : featureType) {
-            String[] features = f.split("\t");
+            String[] features = f.trim().split("\t");
             if (standWords.containsKey(features[0])) {
                 List<Map<String, String>> standWordList = standWords.get(features[0]);
                 for (Map<String, String> standWordMap : standWordList) {
                     if (standWordMap.containsKey("unit") && standWordMap.containsKey("value")) {
                         if (features.length == 2) {
-                            newStandWord = judgment(features, standWordMap, newStandWord, sData);
+                            newStandWord = judgment(features, standWordMap, newStandWord, sData, itemType);
                         } else {
                             if (standWordMap.get("unit").equals(features[2].toLowerCase())) {
-                                newStandWord = judgment(features, standWordMap, newStandWord, sData);
+                                newStandWord = judgment(features, standWordMap, newStandWord, sData, itemType);
                             }
                         }
                     } else if (standWordMap.containsKey("value")) {
                         if (features.length == 2) {
-                            newStandWord = judgment(features, standWordMap, newStandWord, sData);
+                            newStandWord = judgment(features, standWordMap, newStandWord, sData, itemType);
                         }
                     }
                 }
@@ -378,11 +411,11 @@ public class ParamsDataProxy {
         if (flag) {
             addStandWords += smallerStandWord;
         }
-        sData.setSymptom(sData.getSymptom() + "," + addStandWords);
-        System.out.println(sData.getSymptom());
+        addbloodPressure(sData, itemType, addStandWords);
         return sData;
     }
 
+
     /**
      * 将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
      * 除了血压>140/90mmHg类似标准词，其他标准词直接添加在症状后面
@@ -393,7 +426,7 @@ public class ParamsDataProxy {
      * @param sData
      * @return 血压>140/90mmHg或血压小于90/60mmHg或同时返回，在addStandWord()中进一步处理
      */
-    private String judgment(String[] features, Map<String, String> standWordMap, String standWord, SearchData sData) {
+    private String judgment(String[] features, Map<String, String> standWordMap, String standWord, SearchData sData, String itemType) {
         if (hasDigit(features[1])) {
             try {
                 if (">".equals(standWordMap.get("op"))) {
@@ -412,9 +445,10 @@ public class ParamsDataProxy {
                             }
                         }
                     } else {
+                        //"symptom","other","vital","lis","pacs","diag"
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) > Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + proxy(standWordMap.get("standword")));
+                            setStandword(standWordMap, sData, itemType);
                         }
                     }
                 } else if ("<".equals(standWordMap.get("op"))) {
@@ -435,7 +469,7 @@ public class ParamsDataProxy {
                     } else {
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) < Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
+                            setStandword(standWordMap, sData, itemType);
                         }
                     }
                 } else if (">=".equals(standWordMap.get("op"))) {
@@ -456,7 +490,7 @@ public class ParamsDataProxy {
                     } else {
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) >= Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + proxy(standWordMap.get("standword")));
+                            setStandword(standWordMap, sData, itemType);
                         }
                     }
                 } else if ("<=".equals(standWordMap.get("op"))) {
@@ -477,7 +511,7 @@ public class ParamsDataProxy {
                     } else {
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) <= Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
+                            setStandword(standWordMap, sData, itemType);
                         }
                     }
                 }
@@ -488,6 +522,90 @@ public class ParamsDataProxy {
         return standWord;
     }
 
+    /**
+     * 根据不同项目添加标准词
+     *
+     * @param standWordMap
+     * @param sData
+     * @param itemType
+     */
+    private void setStandword(Map<String, String> standWordMap, SearchData sData, String itemType) {
+        switch (itemType) {
+            case "symptom":
+                if (sData.getSymptom().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setSymptom(sData.getSymptom() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+            case "other":
+                if (sData.getOther().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setOther(sData.getOther() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+            case "vital":
+                if (sData.getVital().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setVital(sData.getVital() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+            case "lis":
+                if (sData.getLis().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setLis(sData.getLis() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+            case "pacs":
+                if (sData.getPacs().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setPacs(sData.getPacs() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+            case "diag":
+                if (sData.getDiag().indexOf(proxy(standWordMap.get("standword"))) == -1) {
+                    sData.setDiag(sData.getDiag() + "," + proxy(standWordMap.get("standword")));
+                }
+                break;
+        }
+    }
+
+    /**
+     * 添加血压(血压既满足血压≥140/90mmHg，又满足血压小于90/60mmHg时，只取前者)
+     *
+     * @param sData
+     * @param itemType
+     * @param addStandWords
+     */
+    private void addbloodPressure(SearchData sData, String itemType, String addStandWords) {
+        switch (itemType) {
+            case "symptom":
+                if (sData.getSymptom().indexOf(addStandWords) == -1) {
+                    sData.setSymptom(sData.getSymptom() + "," + addStandWords);
+                }
+                break;
+            case "other":
+                if (sData.getOther().indexOf(addStandWords) == -1) {
+                    sData.setOther(sData.getOther() + "," + addStandWords);
+                }
+                break;
+            case "vital":
+                if (sData.getVital().indexOf(addStandWords) == -1) {
+                    sData.setVital(sData.getVital() + "," + addStandWords);
+                }
+                break;
+            case "lis":
+                if (sData.getLis().indexOf(addStandWords) == -1) {
+                    sData.setLis(sData.getLis() + "," + addStandWords);
+                }
+                break;
+            case "pacs":
+                if (sData.getPacs().indexOf(addStandWords) == -1) {
+                    sData.setPacs(sData.getPacs() + "," + addStandWords);
+                }
+                break;
+            case "diag":
+                if (sData.getDiag().indexOf(addStandWords) == -1) {
+                    sData.setDiag(sData.getDiag() + "," + addStandWords);
+                }
+                break;
+        }
+    }
+
     /**
      * 判断分词后的特征中是否含有数字
      *

bigdata-web/src/main/java/org/diagbot/bigdata/work/ResultDataProxy.java

@@ -30,12 +30,13 @@ public class ResultDataProxy {
         DecimalFormat df = new DecimalFormat("0.####");
         List<FeatureRate> featureList = new ArrayList<>(10);
 
-        Map<String, String> resultMappingVitalMap = ApplicationCacheUtil.getDoc_result_mapping_vital_map();
+//        Map<String, String> resultMappingVitalMap = ApplicationCacheUtil.getDoc_result_mapping_vital_map();
         Map<String, String> resultMappingDiagMap = ApplicationCacheUtil.getDoc_result_mapping_diag_map();
         Map<String, Map<String, ResultMappingFilter>> resultMappingFilterMap = ApplicationCacheUtil.getDoc_result_mapping_filter_map();
+        Map<String, Map<String, String>> synonymMap = ApplicationCacheUtil.getStandard_info_synonym_map();
         for (Map.Entry<String, Float> entry : featuresOrderList) {
             //过滤特征数据, 过滤低于阈值的数据
-            if (!resultFilter(request, searchData, featureType, entry.getKey(), entry.getValue())) {
+            if (!resultFilter(request, searchData, featureType, entry.getKey(), entry.getValue(), synonymMap)) {
                 continue;
             }
             //性别年龄过滤
@@ -58,15 +59,7 @@ public class ResultDataProxy {
             }
             FeatureRate featureRate = new FeatureRate();
             featureRate.setRate(df.format(entry.getValue()));
-            if (FeatureType.parse(featureType) == FeatureType.VITAL) {
-                if (StringUtils.isEmpty(resultMappingVitalMap.get(entry.getKey()))) {
-                    continue;
-                } else {
-                    featureRate.setFeatureName(resultMappingVitalMap.get(entry.getKey()));
-                }
-            } else {
-                featureRate.setFeatureName(entry.getKey());
-            }
+            featureRate.setFeatureName(entry.getKey());
 
             if (FeatureType.parse(featureType) == FeatureType.DIAG) {
                 featureRate.setFeatureName(entry.getKey());
@@ -93,11 +86,16 @@ public class ResultDataProxy {
         return featureList;
     }
 
-    public boolean resultFilter(HttpServletRequest request, BigDataSearchData searchData, String featureType, String result, float threshold) {
+    public boolean resultFilter(HttpServletRequest request, BigDataSearchData searchData, String featureType, String result, float threshold, Map<String, Map<String, String>> synonymMap) {
         //过滤录入条件中已有的特征信息
         if (searchData.getGraphInputs().get(result) != null && FeatureType.parse(featureType) != FeatureType.DIAG) {
             return false;
         }
+        if (FeatureType.parse(featureType) == FeatureType.SYMPTOM) {
+            if (searchData.getGraphInputs().get(synonymMap.get(Constants.word_property_symptom).get(result))!= null) {
+                return false;
+            }
+        }
         //
 //        if (searchData.getFilters().get(result) != null) {
 //            return false;
@@ -141,9 +139,6 @@ public class ResultDataProxy {
         for (Map.Entry<String, Float> entry : map.entrySet()) {
             synonym = convertMap.get(entry.getKey());
             if (synonym != null) {
-                if (isFilter && synonym.equals("阴道出血")) {
-                    System.out.println(entry.getKey() + "-->" + entry.getValue());
-                }
                 if (result.get(synonym) == null) {
                     result.put(synonym, entry.getValue());
                 } else {

bigdata-web/src/main/resources/doc_result_mapping_diag.dict

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bigdata-web/src/main/resources/kl_result_mapping_standword.dict

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bigdata-web/src/test/java/org/diagbot/AddStandWordTest.java

@@ -28,25 +28,62 @@ public class AddStandWordTest {
         //        for (Map.Entry<String, List<Map<String, String>>> entry:entries) {
         //            System.out.println(entry.getKey() + "\t"+ entry.getValue());
         //        }
-//        getStandWordFeatureType();
-//        ApplicationCacheUtil.getKl_result_mapping_standword_map();
-        long startTime = System.currentTimeMillis();
+        //        getStandWordFeatureType();
+        //        ApplicationCacheUtil.getKl_result_mapping_standword_map();
+        /*long startTime = System.currentTimeMillis();
         ApplicationCacheUtil.getKl_result_mapping_standword_map();
         long endCacheTime = System.currentTimeMillis();
         long cacheTime = endCacheTime - startTime;
         System.out.println("处理标准词最终用了:" + cacheTime + "毫秒.");
         SearchData searchData = new SearchData();
 //        searchData.setSymptom("血压14/43mmhg,收缩压140mmhg,血压149/43mmhg");
-        searchData.setSymptom("血压140/?");
+        searchData.setSymptom("病程6月");
         long splitStartTime = System.currentTimeMillis();
         LexemePath<Lexeme> data = ParticipleUtil.participle(searchData.getSymptom());
         ParamsDataProxy paramsDataProxy = new ParamsDataProxy();
-        paramsDataProxy.addStandWord(data, ApplicationCacheUtil.kl_result_mapping_standword_map, searchData);
+        paramsDataProxy.addStandWord(data, ApplicationCacheUtil.kl_result_mapping_standword_map, searchData,"symptom");
         long endTime = System.currentTimeMillis();
         long splitSeconds = endTime - splitStartTime;
         long seconds = endTime - startTime;
         System.out.println("添加标准词使用了:"+splitSeconds + "毫秒.");
-        System.out.println("处理文本总共使用了:"+seconds + "毫秒.");
+        System.out.println("处理文本总共使用了:"+seconds + "毫秒.");*/
+        for (int j = 1; j < 11; j++) {
+
+
+            SearchData searchData = new SearchData();
+            ParamsDataProxy paramsDataProxy = new ParamsDataProxy();
+            searchData.setSymptom("安静时心率98次/分");
+            searchData.setOther("心率156次/分");
+            searchData.setVital("男性43岁");
+            searchData.setLis("Hachinski缺血积分2分");
+            searchData.setPacs("病程9个月");
+            searchData.setDiag("BMI12");
+            String[] items = { searchData.getSymptom(), searchData.getOther(), searchData.getVital()
+                    , searchData.getLis(), searchData.getPacs(), searchData.getDiag() };
+            String[] itemsType = { "symptom", "other", "vital", "lis", "pacs", "diag" };
+            long startTime = System.currentTimeMillis();
+            for (int i = 0; i < items.length; i++) {
+                if (items[i] != null) {
+                    LexemePath<Lexeme> featureData = ParticipleUtil.participle(items[i]);
+                    if (featureData != null) {
+                        paramsDataProxy.addStandWord(featureData, ApplicationCacheUtil.getKl_result_mapping_standword_map(), searchData, itemsType[i]);
+                    }
+                }
+            }
+            System.out.println(searchData.getSymptom());
+            System.out.println(searchData.getOther());
+            System.out.println(searchData.getVital());
+            System.out.println(searchData.getLis());
+            System.out.println(searchData.getPacs());
+            System.out.println(searchData.getDiag());
+            long endTime = System.currentTimeMillis();
+            System.out.println("处理文本总共使用了:" + (endTime - startTime) + "毫秒.");
+            System.out.println("---------------------------第" + j + "次处理---------------------------------");
+        }
+        //        String s = "\tsafGG\tAFASSADG";
+        //        System.out.println(s);
+        //        System.out.println(s.trim());
+
     }
 
     public static void getStandWordFeatureType() throws IOException {
@@ -83,7 +120,7 @@ public class AddStandWordTest {
                 }
             }
             int i = 1;
-            for (Lexeme lexeme:lexemes) {
+            for (Lexeme lexeme : lexemes) {
                 if (lexeme.getProperty().contains(",")) {
                     ApplicationCacheUtil.setProterty(lexeme);
                 }

common-push/pom.xml

@@ -17,6 +17,17 @@
     <url>http://www.example.com</url>
 
     <dependencies>
+        <dependency>
+            <groupId>org.diagbot</groupId>
+            <artifactId>public</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.diagbot</groupId>
+            <artifactId>graph</artifactId>
+            <version>1.0.0</version>
+            <scope>compile</scope>
+        </dependency>
     </dependencies>
 
     <build>

common-push/src/main/java/org/diagbot/common/push/Test.java

@@ -0,0 +1,11 @@
+package org.diagbot.common.push;
+
+/**
+ * @ClassName org.diagbot.common.push.Test
+ * @Description TODO
+ * @Author fyeman
+ * @Date 2019/8/5/005 17:07
+ * @Version 1.0
+ **/
+public class Test {
+}

common-push/src/main/java/org/diagbot/common/push/cache/CacheFileManager.java

@@ -0,0 +1,365 @@
+package org.diagbot.common.push.cache;
+
+import org.diagbot.pub.jdbc.MysqlJdbc;
+import org.diagbot.pub.utils.PropertiesUtil;
+import org.diagbot.pub.utils.security.EncrypDES;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.File;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.sql.Connection;
+import java.sql.ResultSet;
+import java.sql.SQLException;
+import java.sql.Statement;
+import java.util.*;
+
+/**
+ * Created by louhr on 2019/8/16.
+ */
+public class CacheFileManager {
+    Logger logger = LoggerFactory.getLogger(CacheFileManager.class);
+
+    private String user = "root";
+    private String password = "lantone";
+    private String url = "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8";
+
+    private String path = "";
+
+    public static void main(String[] args) {
+        CacheFileManager cacheFileManager = new CacheFileManager();
+        String p = cacheFileManager.getClass().getClassLoader().getResource("").getPath();
+        p = "d:/cache_file/";
+        File file = new File(p);
+        if (!file.exists()) {
+            file.mkdirs();
+        }
+        //自然语言处理
+        cacheFileManager.createNlpCacheFile(p);
+        //大数据
+        cacheFileManager.createBigDataCacheFile(p);
+        //图谱
+        cacheFileManager.createGraphCacheFile(p);
+    }
+
+    public CacheFileManager() {
+        PropertiesUtil propertiesUtil = new PropertiesUtil("nlp.properties");
+        String p = propertiesUtil.getProperty("cache.file.dir");
+        File file = new File(p);
+        if (!file.exists()) {
+            file.mkdirs();
+        }
+        logger.info("cache file path...." + p);
+        path = p;
+    }
+
+    public void createCacheFile() {
+        createNlpCacheFile(path);
+        createGraphCacheFile(path);
+        createBigDataCacheFile(path);
+    }
+
+    public void createNlpCacheFile() {
+        createNlpCacheFile(path);
+    }
+
+    public void createNlpCacheFile(String path) {
+        MysqlJdbc nlpJdbc = new MysqlJdbc(user, password, url);
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            EncrypDES encrypDES = new EncrypDES();
+            //所有词典库 不能用concat_group 大小写不区分
+            String sql = "select l_1.name l_1_name, l_1.type_id type_id, l_2.name l_2_name, l_1.concept_id from kl_library_info l_1\n" +
+                    "                    left join kl_library_info l_2 on l_1.concept_id = l_2.concept_id and l_2.is_concept = 1\n" +
+                    "left join kl_concept kc on l_1.concept_id = kc.id\n" +
+                    "where kc.is_deleted = 'N' ";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            FileWriter fw = new FileWriter(path + "tc.dict");
+
+            Map<String, String> idMap = new HashMap<>(10);
+            Map<String, String> nameMap = new HashMap<>(10);
+            String r1;
+            String r2;
+            String r3;
+            while (rs.next()) {
+                r1 = rs.getString(1);
+                r2 = rs.getString(2);
+                r3 = rs.getString(4);
+                if (idMap.get(r1) == null) {
+                    idMap.put(r1, r2);
+                    nameMap.put(r1, r3);
+                } else if (idMap.get(r1) != null) {
+                    idMap.put(r1, idMap.get(r1) + "," + r2);
+                    nameMap.put(r1, nameMap.get(r1) + "," + r3);
+                }
+            }
+
+            List<Map.Entry<String, String>> libraryList = new ArrayList<Map.Entry<String, String>>(idMap.entrySet());
+            Collections.sort(libraryList, new Comparator<Map.Entry<String, String>>() {
+                public int compare(Map.Entry<String, String> o1, Map.Entry<String, String> o2) {
+                    return o1.getKey().compareTo(o2.getKey());
+                }
+            });
+            for (Map.Entry<String, String> entry : libraryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|9|"
+                        + entry.getValue() + "|" + nameMap.get(entry.getKey())));
+                fw.write("\n");
+            }
+
+            fw.close();
+
+            sql = "SELECT l_1.name l_1_name, l_2.name l_2_name, l_1.type_id FROM kl_library_info l_1 " +
+                    "left join kl_library_info l_2 on l_1.concept_id = l_2.concept_id and l_2.is_concept = '1' " +
+                    "where l_1.is_concept = '0'";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+
+            fw = new FileWriter(path + "synonym.dict");
+            while (rs.next()) {
+                r1 = rs.getString(1);
+                r2 = rs.getString(2);
+                r3 = rs.getString(3);
+                fw.write(encrypDES.encrytor(r1 + "|" + r2 + "|" + r3));
+                fw.write("\n");
+            }
+            fw.close();
+
+            sql = "SELECT l_1.name l_1_name, l_2.name l_2_name FROM kl_relation r " +
+                    "left join kl_concept c1 on r.start_id = c1.id " +
+                    "left join kl_concept c2 on r.end_id = c2.id " +
+                    "left join kl_library_info l_1 on l_1.id = c1.lib_id " +
+                    "left join kl_library_info l_2 on l_2.id = c2.lib_id where r.relation_id = 3";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+
+            libraryList = rsToMap(rs, false);
+
+            fw = new FileWriter(path + "chronic.dict");
+            for (Map.Entry<String, String> entry : libraryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+
+            //推送词典
+            sql = "select k1.lib_name k1_lib_name, k2.lib_name k2_lib_name from kl_relation r " +
+                    "left join kl_concept k1 on k1.id = r.start_id " +
+                    "left join kl_concept k2 on k2.id = r.end_id " +
+                    "where r.relation_id = 19 and k1.is_deleted = 'N' and k2.is_deleted = 'N'";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            libraryList = rsToMap(rs, true);
+
+            fw = new FileWriter(path + "push-tc.dict");
+            for (Map.Entry<String, String> entry : libraryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+
+            fw = new FileWriter(path + "classify.dict");
+            fw.close();
+        } catch (IOException ioe) {
+            ioe.printStackTrace();
+        } catch (SQLException sqle) {
+            sqle.printStackTrace();
+        } catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
+    }
+
+    public void createGraphCacheFile() {
+        createGraphCacheFile(path);
+    }
+
+    public void createGraphCacheFile(String path) {
+        MysqlJdbc nlpJdbc = new MysqlJdbc(user, password, url);
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            //疾病I、II类
+            EncrypDES encrypDES = new EncrypDES();//加密对象
+            String sql = "SELECT con.lib_name, dis.classify from kl_disease dis, kl_concept con where dis.concept_id = con.id";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            FileWriter fw = new FileWriter(path + "graph_diag_classify.dict");
+            String  r2 ,r3;
+            while (rs.next()) {
+                r2 = rs.getString(1);//疾病名称
+                r3 = rs.getString(2);//疾病类别
+                fw.write(encrypDES.encrytor(r2+ "|" + r3));
+                fw.write("\n");
+            }
+            fw.close();
+            //性别年龄
+            sql = "SELECT k1.lib_name, k1.lib_type, kcc.sex_type, kcc.min_age, kcc.max_age \n" +
+                    "FROM kl_concept_common kcc, kl_concept k1 \n" +
+                    "where kcc.concept_id = k1.id \n" +
+                    "and k1.lib_type in (18)";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            fw = new FileWriter(path + "graph_sex_age_filter.dict");
+            String r1, r4, r5;
+            while (rs.next()) {
+                r1 = rs.getString(1);//术语名称
+                r2 = rs.getString(3);//sexType 1:男 2:女 3:都可以
+                r3 = rs.getString(4);//min_age
+                r4 = rs.getString(5);//max_age
+                fw.write(encrypDES.encrytor(r1 + "|" + r2 + "|" + r3+ "|" + r4));
+                fw.write("\n");
+            }
+            fw.close();
+            //体征结果转体征指标
+            sql = "SELECT\n" +
+                    "\ti1.lib_name name1,\n" +
+                    "\ti2.lib_name name2 \n" +
+                    "FROM\n" +
+                    "\t`kl_relation` l \n" +
+                    "\tLEFT JOIN kl_concept i1 ON l.start_id = i1.id \n" +
+                    "\tLEFT JOIN kl_concept i2 ON l.end_id = i2.id \n" +
+                    "where l.relation_id=19 AND i1.lib_type=35 AND i2.lib_type=33 AND l.is_deleted='N'";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            fw = new FileWriter(path + "graph_vital_convert.dict");
+            while (rs.next()) {
+                r1 = rs.getString(1);//体征结果
+                r2 = rs.getString(2);//体征指标
+                fw.write(encrypDES.encrytor(r1 + "|" + r2));
+                fw.write("\n");
+            }
+            fw.close();
+            //疾病科室信息
+            sql = "SELECT k1.lib_name diag_name, k2.lib_name dept_name FROM kl_concept_common kcc, kl_concept k1, kl_concept k2 " +
+                    "where kcc.concept_id = k1.id and kcc.dept_id = k2.id " +
+                    "and k1.lib_type = 18 and kcc.dept_id  is not null";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            List<Map.Entry<String, String>> libaryList = rsToMap(rs, true);
+            fw = new FileWriter(path + "graph_diag_2_dept.dict");
+            for (Map.Entry<String, String> entry : libaryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+
+            sql = "SELECT g.diag_level1,g.diag_level2,g.diag_level3 FROM `kl_disease_normalize` g ";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            fw = new FileWriter(path + "graph_diag_normalize.dict");
+            while (rs.next()) {
+                r1 = rs.getString(1);
+                r2 = rs.getString(2);
+                r3 = rs.getString(3);
+                fw.write(encrypDES.encrytor(r1+ "|" + r2+ "|" + r3));
+                fw.write("\n");
+            }
+            fw.close();
+        } catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
+    }
+
+    public void createBigDataCacheFile() {
+        createBigDataCacheFile(path);
+    }
+
+    public void createBigDataCacheFile(String path) {
+        MysqlJdbc nlpJdbc = new MysqlJdbc(user, password, url);
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            EncrypDES encrypDES = new EncrypDES();
+            //疾病科室
+            String sql = "SELECT k1.lib_name diag_name, k2.lib_name dept_name FROM kl_concept_common kcc, kl_concept k1, kl_concept k2 " +
+                    "where kcc.concept_id = k1.id and kcc.dept_id = k2.id " +
+                    "and k1.lib_type = 18 and kcc.dept_id  is not null";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            List<Map.Entry<String, String>> libraryList = rsToMap(rs, true);
+
+            FileWriter fw = new FileWriter(path + "bigdata_diag_2_dept.dict");
+            for (Map.Entry<String, String> entry : libraryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+
+            //性别年龄
+            sql = "SELECT k1.lib_name, k1.lib_type, kcc.sex_type, kcc.min_age, kcc.max_age " +
+                    "FROM kl_concept_common kcc, kl_concept k1 " +
+                    "where kcc.concept_id = k1.id " +
+                    "and k1.lib_type in (1, 18)";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            fw = new FileWriter(path + "bigdata_sex_age_filter.dict");
+
+            String r1, r2, r3, r4, r5;
+            while (rs.next()) {
+                r1 = rs.getString(1);
+                r2 = rs.getString(2);
+                r3 = rs.getString(3);
+                r4 = rs.getString(4);
+                r5 = rs.getString(5);
+                if ("18".equals(r2)) {
+                    r2 = "2";
+                }
+                fw.write(encrypDES.encrytor(r1 + "|" + r2 + "|" + r3 + "|" + r4 + "|" + r5));
+                fw.write("\n");
+            }
+            fw.close();
+
+            sql = "SELECT lib_name FROM kl_concept WHERE is_deleted = 'N' AND lib_type = 70 AND lib_name regexp '[0-9]'";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+
+            fw = new FileWriter(path + "bigdata_value_analyze.dict");
+            while (rs.next()) {
+                fw.write(encrypDES.encrytor(rs.getString(1)));
+                fw.write("\n");
+            }
+            fw.close();
+        } catch (IOException ioe) {
+            ioe.printStackTrace();
+        } catch (SQLException sqle) {
+            sqle.printStackTrace();
+        }  catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
+    }
+
+    private List<Map.Entry<String, String>> rsToMap(ResultSet rs, boolean isJoin) throws SQLException{
+        String r1 = "";
+        String r2 = "";
+        Map<String, String> libraryMap = new HashMap<>(10);
+        while (rs.next()) {
+            r1 = rs.getString(1);
+            r2 = rs.getString(2);
+            if (libraryMap.get(r1) == null) {
+                libraryMap.put(r1, r2);
+            } else if (isJoin && libraryMap.get(r1) != null) {
+                libraryMap.put(r1, libraryMap.get(r1) + "," + r2);
+            }
+        }
+
+        List<Map.Entry<String, String>> libraryList = new ArrayList<Map.Entry<String, String>>(libraryMap.entrySet());
+        Collections.sort(libraryList, new Comparator<Map.Entry<String, String>>() {
+            public int compare(Map.Entry<String, String> o1, Map.Entry<String, String> o2) {
+                return o1.getKey().compareTo(o2.getKey());
+            }
+        });
+
+        return libraryList;
+    }
+}

common-push/src/main/java/org/diagbot/common/push/filter/ClassifyDiag.java

@@ -0,0 +1,524 @@
+package org.diagbot.common.push.filter;
+
+import com.alibaba.fastjson.JSONObject;
+import org.apache.commons.lang3.StringUtils;
+import org.diagbot.common.work.FeatureRate;
+import org.diagbot.common.work.ResponseData;
+import org.diagbot.graph.util.CacheUtil;
+
+import java.text.DecimalFormat;
+import java.util.*;
+import java.util.stream.Stream;
+
+/**
+ * Created by kwz on 2019/8/5.
+ */
+public class ClassifyDiag {
+    //诊断-->部门
+    Map<String, String>  diagDepartCache     = CacheUtil.getDiagDepartCache();
+    //get diagClassifyCache
+    Map<String, String>  diagClassifyCache   = CacheUtil.getDiagClassifyCache();
+    //每个诊断所在的级别缓存
+    Map<String, Integer> diagClassifyJiCache = CacheUtil.getDiagClassifyJiCache();
+
+   /* public static void main(String[] args) {
+
+        List<String> disList = new LinkedList<>();
+        String[] disArray = {"急性胰腺炎","冠心病","急性冠状动脉综合征","急性非ST段抬高型心肌梗死","急性ST段抬高型心肌梗死"
+        ,"三度房室传导阻滞","心力衰竭","急性心力衰竭"};
+         disList = Arrays.asList(disArray);
+        System.out.println("输入的诊断"+disList);
+        List<FeatureRate> inintFeature = new ArrayList<>();
+        Double inintNumber = 0.95;
+        String rate = "";
+        for (String dis:disList) {
+            FeatureRate featureRate = new FeatureRate();
+            featureRate.setFeatureName(dis);
+            inintNumber = inintNumber - 0.1;
+            rate = String.valueOf(inintNumber);
+            featureRate.setRate(rate);
+            inintFeature.add(featureRate);
+        }
+
+        ClassifyDiag classifyDiag = new ClassifyDiag();
+        List<FeatureRate> classify = classifyDiag.diagClassify(inintFeature);
+        System.out.println("hao hai you");
+        for (FeatureRate d:classify) {
+            System.out.println(d.getFeatureName()+"\t"+d.getRate()+"\t"+d.getExtraProperty());
+        }
+
+    }*/
+
+    /**
+     * 根据诊断依据规则过滤诊断
+     * @param graphResponseData 把过滤的诊断包装在这个对象里
+     * @param graphFeatures 过滤前的诊断结果
+     * @return 返回过滤后的诊断结果
+     */
+    public List<FeatureRate> filterDiag(ResponseData graphResponseData,List<FeatureRate> graphFeatures){
+        //根据诊断依据规则过滤掉的诊断列表
+        List<String> excludeDiag = graphResponseData.getExcludeDiag();
+        //将需要排除的诊断从列表中删除
+        List<FeatureRate> updateFeatures = new ArrayList<>();
+        if(excludeDiag != null){
+            for(int j = 0;j<graphFeatures.size();j++){
+                if(excludeDiag.indexOf(graphFeatures.get(j).getFeatureName()) == -1){
+                    updateFeatures.add(graphFeatures.get(j));
+                }
+            }
+            return updateFeatures;
+        }else {
+            return graphFeatures;
+        }
+
+    }
+
+    /**
+     * 诊断归一
+     * @param updateFeatures 归一前的诊断
+     * @return 归一后的诊断
+     */
+    public List<FeatureRate> diagClassify(List<FeatureRate> updateFeatures){
+        List<FeatureRate> finalDiagList = new LinkedList<>();//最终返回
+        List<String> highDiagList = new LinkedList<>();//警惕集合
+        List<String> queDiagList = new LinkedList<>();//确诊集合
+        List<String> bigDiagList = new LinkedList<>();//可能诊断集合
+        if(updateFeatures != null && updateFeatures.size()>0){
+            for(FeatureRate featureRate:updateFeatures){
+                String featureName = featureRate.getFeatureName();
+                String desc = featureRate.getDesc();
+                Map<String,Object> d = new HashMap<>();
+                if(desc != null){
+                    JSONObject jsonObject = JSONObject.parseObject(desc);
+                    d = jsonObject;
+                    if(d.keySet().size() == 1 && "警惕".equals(d.keySet().toArray()[0])){
+                        highDiagList.add(featureName);
+                    }else {
+                        queDiagList.add(featureName);
+                    }
+                }else {
+                    bigDiagList.add(featureName);
+                }
+            }
+        }
+        //先把警惕的加进去
+        if(highDiagList.size()>0){
+            for(int j =0;j<updateFeatures.size();j++){
+                FeatureRate featureRate = updateFeatures.get(j);
+                String featureName = featureRate.getFeatureName();
+                int i = highDiagList.indexOf(featureName);
+                if(i >= 0){
+                    finalDiagList.add(featureRate);
+                }
+            }
+        }
+        /**
+         * 这里处理一下可能诊断剔除的功能
+         * 如果图谱推出的诊断和可能诊断有层级关系，就把对应的可能诊断剔除
+         */
+        Set<String> queSet =null;
+        List<String> newBIgDiagList = this.removeKeng(queDiagList, bigDiagList);
+        System.out.println("图谱归一前数据 ："+queDiagList);
+        if(queDiagList != null && queDiagList.size()>0){
+            //图谱归一 ,图谱sign =0,大数据sign = 1
+            queSet = this.diagProcess(queDiagList,0);
+            System.out.println("图谱归一后的数据    ："+queSet);
+            if(queSet != null && queSet.size()>0){
+                for (String queDis:queSet) {
+                    if(queDiagList.indexOf(queDis)>=0){ //可以找到，就取出来，用原来的
+                        FeatureRate feature = this.getFeature(updateFeatures, queDis);
+                        feature.setExtraProperty(diagDepartCache.get(queDis));
+                        finalDiagList.add(feature);
+                    }else {
+                        FeatureRate featureRate = new FeatureRate();
+                        featureRate.setFeatureName(queDis);
+                        featureRate.setDesc("{\"确诊\":\"\"}");
+                        featureRate.setExtraProperty(diagDepartCache.get(queDis));
+                        featureRate.setSource("neo4j");
+                        finalDiagList.add(featureRate);
+                    }
+                }
+            }
+        }
+
+
+        if(newBIgDiagList!= null && newBIgDiagList.size()>0){
+            //大数据的可能诊断归一和排序
+            List<FeatureRate> featureRates = this.sortFeatureList(newBIgDiagList, updateFeatures);
+            //把可能诊断中和图谱相同的诊断去除
+            if(featureRates != null && featureRates.size()>0 && queSet !=null){
+                for (FeatureRate f:featureRates) {
+                    if(queSet.contains(f.getFeatureName())){
+                        featureRates.remove(f);
+                        continue;
+                    }
+                }
+            }
+            finalDiagList.addAll(featureRates);
+        }
+
+        return finalDiagList;
+
+    }
+
+    /**
+     * 诊断排序（诊断分为I类和II类，I类在前，II类在后，没有分类的诊断认为是I类）
+     * @param updateFeatureRates  //入参（通过过滤条件过滤后）
+     * @return
+     */
+    public List<FeatureRate> sortDiag(List<FeatureRate> updateFeatureRates){
+        Map<String, String> diagSortCache = CacheUtil.getDiagSortCache();
+        List<String> finalDiagList = new LinkedList<>();
+        List<String> neoDiagList = new LinkedList<>();
+        List<String> bigDataIDiagList = new LinkedList<>();
+        List<String> bigDataIIDiagList = new LinkedList<>();
+        List<FeatureRate> finalDiagFeature = new LinkedList<>();
+        if(updateFeatureRates != null || updateFeatureRates.size()>0){
+            for (FeatureRate feature:updateFeatureRates) {
+                String featureName = feature.getFeatureName();
+                String source = feature.getSource();
+                if("neo4j".equals(source)){
+                    neoDiagList.add(featureName);
+                }else {
+                    String s = diagSortCache.get(featureName);
+                    if(StringUtils.isNotEmpty(s)){
+                        if("Ⅰ".equals(s)){
+                            bigDataIDiagList.add(featureName);
+                        }else if("Ⅱ".equals(s)){
+                            bigDataIIDiagList.add(featureName);
+                        }
+                    }else {
+                        bigDataIDiagList.add(featureName);
+                    }
+                }
+            }
+        }
+        finalDiagList.addAll(neoDiagList);
+        finalDiagList.addAll(bigDataIDiagList);
+        finalDiagList.addAll(bigDataIIDiagList);
+        if(finalDiagList != null && finalDiagList.size()>0){
+            for (String diag:finalDiagList){
+                for (FeatureRate f:updateFeatureRates) {
+                    if(diag.equals(f.getFeatureName())){
+                        finalDiagFeature.add(f);
+                        break;
+                    }
+                }
+            }
+        }
+        return finalDiagFeature;
+    }
+
+    /**
+     * 去除可能诊断和确诊有关系的诊断
+     * @param queDiagList
+     * @param bigDiagList
+     * @return
+     */
+    public List<String> removeKeng(List<String> queDiagList,List<String> bigDiagList){
+        List<String> bigList = new ArrayList<>();
+        Set<String> queAll = new HashSet<>();
+        if(queDiagList.size()>0 && bigDiagList.size()>0){
+            for (String dis:queDiagList) {
+                String s = diagClassifyCache.get(dis);
+                if(s != null){
+                    queAll.add(s);
+                }
+                queAll.add(dis);
+                List<Object> key = this.getKey(diagClassifyCache, dis);
+                if(key != null && key.size()>0){
+                    for (Object o:key) {
+                        queAll.add(o.toString());
+                        List<Object> key1 = this.getKey(diagClassifyCache, o.toString());
+                        if(key1 !=null && key1.size()>0){
+                            for (Object o1:key1
+                                 ) {
+                                queAll.add(o1.toString());
+                            }
+                        }
+                    }
+
+                }
+
+            }
+        }
+        System.out.println(queAll);
+        String[] strings = queAll.stream().toArray(String[]::new);
+        if(bigDiagList != null && bigDiagList.size()>0){
+            for (String dis:bigDiagList) {
+                if(Arrays.asList(strings).indexOf(dis) == -1){
+                    bigList.add(dis);
+                }
+            }
+        }
+        return bigList;
+    }
+
+
+
+
+
+    /**
+     * 诊断归一和排序
+     * @param disList
+     * @return
+     */
+    public Set<String> diagProcess(List<String> disList,int sign){
+        Set<String> first = new HashSet<>();
+        Set<String> second= new HashSet<>();
+        Set<String> third= new HashSet<>();
+        Set<String> other= new HashSet<>();
+
+        /**
+         * 分级
+         * 初始化每个病出现的次数为0
+         */
+        Map<String, Integer> children_cnt = new HashMap<>();
+        for (String dis:disList) {
+            Integer ji = diagClassifyJiCache.get(dis);
+            if(ji != null){
+                if(1 == ji){
+                    first.add(dis);
+                    children_cnt.put(dis,0);
+                }else if(2 == ji){
+                    second.add(dis);
+                    children_cnt.put(dis,0);
+                }else if(3 == ji){
+                    third.add(dis);
+                    children_cnt.put(dis,0);
+                }
+            }else {
+                other.add(dis);
+            }
+        }
+        /**
+         * 从孙子找父亲，根据父亲找爷爷
+         */
+        if(third != null && third.size()>0){
+            for (String dis:third) {
+                String s = diagClassifyCache.get(dis);
+                Integer count = children_cnt.get(s);
+                if(s != null){
+                    children_cnt.put(s,(count == null)?1:count+1);
+                    second.add(s);
+                }
+
+            }
+        }
+
+        if(second != null && second.size()>0){
+            for (String dis:second) {
+                String s = diagClassifyCache.get(dis);
+                Integer count = children_cnt.get(s);
+                if(s != null){
+                    children_cnt.put(s,(count == null)?1:count+1);
+                    first.add(s);
+                }
+            }
+        }
+        List<String> pushDiag = new ArrayList<>();
+        //从顶级往下级依次看
+        for (String dis:first) {
+            Integer count = children_cnt.get(dis);
+            if(count == 0){
+                pushDiag.add(dis);
+            }else if(count == 1){
+                List<Object> key = this.getKey(diagClassifyCache, dis);
+                for (String diss:second) {
+                    Integer c2 = children_cnt.get(diss);
+                    if(key.contains(diss)){
+                        if(c2 == 0){
+                            pushDiag.add(diss);
+                        }else if(c2 == 1){
+                            List<Object> key1 = this.getKey(diagClassifyCache, diss);
+                            for (String disss:third) {
+                                if(key1.contains(disss)){
+                                    pushDiag.add(disss);
+                                }
+                            }
+                        }else if(c2 >1){
+                            pushDiag.add(diss);
+                        }
+                    }
+
+                }
+            }else if(count >1){
+                pushDiag.add(dis);
+            }
+
+        }
+        pushDiag.addAll(other); //归一后的
+
+        Set<String> finalList = new LinkedHashSet<>();
+        if(sign == 0){
+            finalList.addAll(pushDiag);
+        }else if(sign == 1){
+            for (String dis:disList) {
+                int i = pushDiag.indexOf(dis);
+                if(i >= 0){
+                    finalList.add(dis);
+
+                }else {
+                    List<Object> testList= new ArrayList<>();
+                    String s = diagClassifyCache.get(dis);
+                    if(StringUtils.isNotEmpty(s)){
+                        testList.add(s);
+                    }
+                    List<Object> key = this.getKey(diagClassifyCache, dis);
+                    boolean b = testList.addAll(key);
+                    for (Object dis1:testList) {
+                        if(pushDiag.indexOf(dis1)>=0){
+                            finalList.add(dis1.toString());
+
+                        }
+                    }
+                }
+            }
+        }
+
+        return finalList;
+
+    }
+
+    /**
+     * 根据rate排序
+     * @param diss 大数据可能诊断列表
+     * @param updates 所有推送的诊断
+     * @return 排好序并且归一的可能诊断列表
+     */
+    public List<FeatureRate> sortFeatureList(List<String> diss,List<FeatureRate> updates){
+        DecimalFormat df = new DecimalFormat("0.####");
+       List<FeatureRate> sortFeatures = new LinkedList<>();
+        Set<String> strings = this.diagProcess(diss,1);
+
+        Map<String,Double> disRate = new HashMap<>();
+        //归一确诊
+        if(diss!= null &&diss.size()>0){
+            //归一后的确诊（图谱出来的）
+
+            if(strings != null && strings.size()>0){
+                for (String queDis:strings) {
+                    List<Object> testCollect = new ArrayList<>();
+//                    FeatureRate feature = classifyDiag.getFeature(inintFeature, queDis);
+                    //如果能找到就把相关联的rate加起来
+                    testCollect.add(queDis);
+
+                    String s = null;
+                    s= diagClassifyCache.get(queDis);
+                    if(s != null){
+                        testCollect.add(s);
+                        s = diagClassifyCache.get(s);
+                        if(s != null){
+                            testCollect.add(s);
+                        }
+                    }
+                    List<Object> key =null;
+                    key = this.getKey(diagClassifyCache, queDis);
+                    testCollect.addAll(key);
+                    if(key != null && key.size()>0){
+                        for (Object o:key) {
+                            key = this.getKey(diagClassifyCache,o.toString());
+                            if(key!= null){
+                                testCollect.addAll(key);
+                            }
+                        }
+                    }
+                    Double count = 0.0;
+                    for (String dis:diss) {
+                        if(testCollect.indexOf(dis) >= 0){
+                            FeatureRate feature1 = this.getFeature(updates, dis);
+                            String rate1 = feature1.getRate();
+                            count = count+Double.parseDouble(rate1);
+                        }
+                    }
+                    disRate.put(queDis,count);
+                }
+            }
+
+        }
+        //根据rate排序
+        List<Map.Entry<String,Double>> list = new ArrayList<>(disRate.entrySet());
+        Collections.sort(list, new Comparator<Map.Entry<String, Double>>() {
+            @Override
+            public int compare(Map.Entry<String, Double> o1, Map.Entry<String, Double> o2) {
+                return o2.getValue().compareTo(o1.getValue());
+            }
+        });
+        for (Map.Entry<String,Double> s:list) {
+            System.out.println(s.getKey()+"\t"+s.getValue());
+            FeatureRate featureRate = new FeatureRate();
+            featureRate.setRate(df.format(s.getValue()));
+            featureRate.setFeatureName(s.getKey());
+            featureRate.setExtraProperty(diagDepartCache.get(s.getKey()));
+            sortFeatures.add(featureRate);
+        }
+
+        return sortFeatures;
+    }
+
+    /**
+     * 根据诊断名找到这个feature
+     * @param updateFeatures
+     * @param disName
+     * @return
+     */
+    public FeatureRate getFeature(List<FeatureRate> updateFeatures,String disName){
+        FeatureRate f = new FeatureRate();
+        for (FeatureRate fe:updateFeatures){
+            if(disName.equals(fe.getFeatureName())){
+                f = fe;
+            }
+        }
+        return f;
+    }
+
+    /**
+     * dis找大类
+     * @param inputs
+     * @return
+     */
+    public List<String> getDisList(List<String> inputs){
+        List<String> newDiagList = new ArrayList<>();
+        if(inputs!= null && inputs.size()>0){
+            for (String dis:inputs) {
+                String s = diagClassifyCache.get(dis);
+                if(StringUtils.isNotEmpty(s)){
+                    newDiagList.add(s);
+                }else {
+                    newDiagList.add(dis);
+                }
+
+            }
+        }
+        return newDiagList;
+    }
+
+    /**
+     * 统计列表中每个字符出现的次数
+     * @param inputs 输入列表
+     * @return
+     */
+    public Map<String,Integer> fildCount(List<String> inputs){
+        Map<String,Integer> map = new HashMap<>();
+        for (String dis:inputs) {
+            Integer count = map.get(dis);
+            map.put(dis,(count == null)?1:count+1);
+        }
+        return map;
+    }
+
+    public List<Object>  getKey(Map map, Object value){
+        Set set = map.entrySet(); //通过entrySet()方法把map中的每个键值对变成对应成Set集合中的一个对象
+        Iterator<Map.Entry<Object, Object>> iterator = set.iterator();
+        List<Object> arrayList = new ArrayList();
+        while(iterator.hasNext()){
+            //Map.Entry是一种类型，指向map中的一个键值对组成的对象
+            Map.Entry<Object, Object> entry = iterator.next();
+            if(entry.getValue().equals(value)){
+                arrayList.add(entry.getKey());
+            }
+        }
+        return arrayList;
+    }
+
+}

common-service/src/main/java/org/diagbot/common/work/ResponseData.java

@@ -21,6 +21,8 @@ public class ResponseData {
     private List<FeatureRate> pacs = new ArrayList<>(10);
     private List<FeatureRate> history = new ArrayList<>(10);
 
+    private List<FeatureRate> beforeCombineDis = new ArrayList<>(10);
+
     private Map<String, Filnlly> treat = new HashMap<>();
     private List<FeatureRate> graphWords = new ArrayList<>(10);
     private List<MedicalIndication> medicalIndications;//量表和指标推送
@@ -150,4 +152,12 @@ public class ResponseData {
     public void setHistory(List<FeatureRate> history) {
         this.history = history;
     }
+
+    public List<FeatureRate> getBeforeCombineDis() {
+        return beforeCombineDis;
+    }
+
+    public void setBeforeCombineDis(List<FeatureRate> beforeCombineDis) {
+        this.beforeCombineDis = beforeCombineDis;
+    }
 }

graph-web/src/main/java/org/diagbot/graphWeb/work/FilterSortDiag.java

@@ -15,6 +15,7 @@ import java.util.*;
  */
 public class FilterSortDiag {
     Logger logger = LoggerFactory.getLogger(FilterSortDiag.class);
+
     /**
      * 过滤诊断
      */

graph-web/src/main/java/org/diagbot/graphWeb/work/GraphCalculate.java

@@ -65,8 +65,7 @@ public class GraphCalculate {
         logger.info("从分词系统接收到的词 :" + ss);
         System.out.println("Participle takes: " + (System.currentTimeMillis()-starttime)/1000d + 's');
 
-        String[] featureTypes = searchData.getFeatureType().split(",");
-        List<String> featureTypeList = Arrays.asList(featureTypes);
+        List<String> featureTypeList = Arrays.asList(searchData.getFeatureTypes());
         logger.info("featureTypeList : " + featureTypeList);
         inputList.addAll(ss);
         if(neo4jAPI == null){

graph-web/src/main/resources/url.properties

@@ -1,5 +1,5 @@
-highrisk.http.url=http://192.168.2.186:5004/knowledge/getHighRisk
-lisPacs.http.url=http://192.168.2.186:5004/knowledge/getLisPacs
-disease.http.url=http://192.168.2.186:5004/knowledge/getDisease
+highrisk.http.url=http://192.168.2.234:5004/knowledge/getHighRisk
+lisPacs.http.url=http://192.168.2.234:5004/knowledge/getLisPacs
+disease.http.url=http://192.168.2.234:5004/knowledge/getDisease
 #lisPacs.http.url=http://192.168.3.9:5004/knowledge/getLisPacs
 #highrisk.http.url=http://192.168.3.9:5004/knowledge/getHighRisk

graph/src/main/java/org/diagbot/graph/jdbc/Neo4jAPI.java

@@ -1478,7 +1478,11 @@ public class Neo4jAPI {
                             //                            Map<String, String> bigSubDrugs = new DrugsPattern().bigSubDrugs(drugsName);
                             Map<String, String> bigSubDrugs = drugsPattern.bigSubDrugs(drugsName);
                             drugs.setBigdrugsName(bigSubDrugs.get("big"));
-                            drugs.setSubdrugsName(bigSubDrugs.get("sub"));
+                            drugs.setSubdrugsName("");
+                            // 如果大类和小类相等，则不推小类
+                            if (!bigSubDrugs.get("sub").equals(drugs.getBigdrugsName())) {
+                                drugs.setSubdrugsName(bigSubDrugs.get("sub"));
+                            }
                             LinkedList<Medicition> medicitionsList = new LinkedList<>();
                             LinkedHashMap<String, String> meditionRate = w.getValue();
                             if ("忌用".equals(drugsUseMap.get(bigSubDrugs.get("big"))) || "忌用".equals(drugsUseMap.get(bigSubDrugs.get("sub")))) {
@@ -2687,7 +2691,7 @@ public class Neo4jAPI {
 
         } catch (Exception ex) {
             ex.printStackTrace();
-            System.out.println("返回带得分需要计算的量表时出了问题！---->getScaleCalc");
+            logger.error("返回带得分需要计算的量表出了问题！---->getScaleCalc2");
         } finally {
             CloseSession(session);
             return scaleStructure;
@@ -2746,6 +2750,10 @@ public class Neo4jAPI {
                     scaleStructure.put("scaleName", scaleName);
                 }
 
+                if (index.contains("-")) {
+                    index = index.split("-")[0];
+                }
+
                 JSONObject detail = new JSONObject();
                 detail.put("detailName", feature);
                 detail.put("state", 0);
@@ -2779,7 +2787,7 @@ public class Neo4jAPI {
             }
         } catch (Exception ex) {
             ex.printStackTrace();
-            System.out.println("返回不带得分不需要计算的量表出了问题！---->getScaleNoCalc");
+            logger.error("返回不带得分不需要计算的量表出了问题！---->getScaleNoCalc");
         } finally {
             CloseSession(session);
             return scaleStructure;

graph/src/main/java/org/diagbot/graph/util/CacheUtil.java

@@ -1,5 +1,6 @@
 package org.diagbot.graph.util;
 
+import org.apache.commons.lang3.StringUtils;
 import org.diagbot.nlp.participle.cfg.Configuration;
 import org.diagbot.nlp.participle.cfg.DefaultConfig;
 
@@ -8,69 +9,167 @@ import java.util.List;
 import java.util.Map;
 
 public class CacheUtil {
-    public static Map<String,String> lexionMap=null;
     public static Map<String,Map<String,String>> sexAgeMap=null;
     public static Map<String,String> vitalMap=null;
     public static Map<String,String> disgSortMap=null;
-    public static Map<String,String> getDiagSortCache(){
-        String path = "diagSort.dict";
+    public static Map<String,String> diagClassifyMap = null;
+    public static Map<String,Integer> diagClassifyJiMap = null;
+    //诊断科室衍射
+    public static Map<String, String> doc_result_mapping_diag_map = null;
+
+    //疾病科室，获取缓存
+    public static Map<String,String> getDiagDepartCache(){
+        if (doc_result_mapping_diag_map == null) {
+            createDiagDepartCache();
+        }
+        return doc_result_mapping_diag_map;
+    }
+
+    public static Map<String,String> createDiagDepartCache(){
         Configuration configuration = new DefaultConfig();
-        if(disgSortMap == null){
-            disgSortMap = new HashMap<>();
-            List<String> contentList = configuration.readFileContents(path);
-            for (String s:contentList) {
-                String[] splits = s.split("\\|");
-                String diagName = splits[0];
-                String diagType = splits[1];
-                disgSortMap.put(diagName,diagType);
+        doc_result_mapping_diag_map = new HashMap<>();
+        List<String> contentList = configuration.readFileContents("graph_diag_2_dept.dict");
+        for (String s:contentList) {
+            String[] splits = s.split("\\|");
+            doc_result_mapping_diag_map.put(splits[0],splits[1]);
+        }
+        return doc_result_mapping_diag_map;
+    }
+
+    //疾病分级解析，获取缓存
+    public static Map<String,Integer> getDiagClassifyJiCache(){
+        if (diagClassifyJiMap == null) {
+            createDiagClassifyJiCache();
+        }
+        return diagClassifyJiMap;
+    }
+
+    public static Map<String,Integer> createDiagClassifyJiCache(){
+        Configuration configuration = new DefaultConfig();
+        diagClassifyJiMap = new HashMap<>();
+        List<String> contentList = configuration.readFileContents("graph_diag_normalize.dict");
+        String diagName =null,bigdiagName=null;
+        String[] diagSort =null;String[] split = null;
+        for (String s:contentList) {
+            String[] splits = s.split("\\|");
+            if (splits.length >= 2) {
+                diagName = splits[0].trim();//疾病本体
+                bigdiagName = splits[1].trim();//疾病大类
+                split = bigdiagName.split("\\、");
+                for (String dis:split) {
+                    diagClassifyJiMap.put(dis, 2);
+                }
+                diagClassifyJiMap.put(diagName,1);
+                if (splits.length == 3) {
+                    diagSort = splits[2].split("\\、");
+                    for (String dis : diagSort) {
+                        if (StringUtils.isNotEmpty(dis.trim())) {
+                            diagClassifyJiMap.put(dis.trim(), 3);
+                        }
+                    }
+                }
             }
         }
-        return disgSortMap;
+        return diagClassifyJiMap;
+    }
+
+    //疾病归一解析，获取缓存
+    public static Map<String,String> getDiagClassifyCache(){
+        if (diagClassifyMap == null) {
+            createDiagClassifyCache();
+        }
+        return diagClassifyMap;
     }
-    public static Map<String,String> getLexionCache(){
-        String path = "lexicon.dict";
+
+    public static Map<String,String> createDiagClassifyCache(){
         Configuration configuration = new DefaultConfig();
-        if(lexionMap == null){
-            lexionMap = new HashMap<>();
-            List<String> contentList = configuration.readFileContents(path);
-            for (String s:contentList) {
-                String[] splits = s.split("\\|");
-                lexionMap.put(splits[0],splits[1]);
+        diagClassifyMap = new HashMap<>();
+        List<String> contentList = configuration.readFileContents("graph_diag_normalize.dict");
+        String diagName =null,bigdiagName=null;
+        String[] diagSort =null;String[] split =null;
+        for (String s:contentList) {
+            String[] splits = s.split("\\|");
+            if (splits.length >= 2) {
+                diagName = splits[0].trim();//疾病本体
+                bigdiagName = splits[1].trim();//疾病大类
+                split = bigdiagName.split("\\、");
+                for (String dis:split
+                        ) {
+                    diagClassifyMap.put(dis, diagName);
+                }
+
+                if (splits.length == 3) {
+                    diagSort = splits[2].split("\\、");
+                    for (String dis : diagSort) {
+                        if (StringUtils.isNotEmpty(dis.trim())) {
+                            diagClassifyMap.put(dis.trim(), bigdiagName);
+                        }
+                    }
+                }
             }
+        }
+        return diagClassifyMap;
+    }
 
+    public static Map<String,String> getDiagSortCache(){
+        if(disgSortMap == null){
+            createDiagSortCache();
+        }
+        return disgSortMap;
+    }
+    public static Map<String,String> createDiagSortCache(){
+        disgSortMap = new HashMap<>();
+
+        Configuration configuration = new DefaultConfig();
+        List<String> contentList = configuration.readFileContents("graph_diag_classify.dict");
+        for (String s:contentList) {
+            String[] splits = s.split("\\|");
+            String diagName = splits[0];
+            String diagType = splits[1];
+            disgSortMap.put(diagName,diagType);
         }
-        return lexionMap;
+        return disgSortMap;
     }
+
     public static Map<String,Map<String,String>> getSexAgeCache(){
-        String path = "sexAge.dict";
+        if (sexAgeMap == null) {
+            createSexAgeCache();
+        }
+        return sexAgeMap;
+    }
+
+    public static Map<String,Map<String,String>> createSexAgeCache(){
         Configuration configuration = new DefaultConfig();
-        if(sexAgeMap == null){
-            sexAgeMap = new HashMap<>();
-            List<String> contentList = configuration.readFileContents(path);
-            for (String s:contentList) {
-                Map<String,String> contentMap = new HashMap<>();
-                String[] splits = s.split("\\|");
-                String sexTyep = splits[1];
-                String min_age = splits[2];
-                String max_age = splits[3];
-                contentMap.put("sexType",sexTyep);
-                contentMap.put("min_age",min_age);
-                contentMap.put("max_age",max_age);
-                sexAgeMap.put(splits[0],contentMap);
-            }
+        sexAgeMap = new HashMap<>();
+        List<String> contentList = configuration.readFileContents("graph_sex_age_filter.dict");
+        for (String s:contentList) {
+            Map<String,String> contentMap = new HashMap<>();
+            String[] splits = s.split("\\|");
+            String sexTyep = splits[1];
+            String min_age = splits[2];
+            String max_age = splits[3];
+            contentMap.put("sexType",sexTyep);
+            contentMap.put("min_age",min_age);
+            contentMap.put("max_age",max_age);
+            sexAgeMap.put(splits[0],contentMap);
         }
         return sexAgeMap;
     }
+
     public static Map<String,String> getVitalCache(){
-        String path = "vital.dict";
+        if (vitalMap == null) {
+            createVitalCache();
+        }
+        return vitalMap;
+    }
+
+    public static Map<String,String> createVitalCache(){
         Configuration configuration = new DefaultConfig();
-        if(vitalMap == null){
-            vitalMap = new HashMap<>();
-            List<String> contentList = configuration.readFileContents(path);
-            for (String s:contentList) {
-                String[] splits = s.split("\\|");
-                vitalMap.put(splits[0],splits[1]);
-            }
+        vitalMap = new HashMap<>();
+        List<String> contentList = configuration.readFileContents("graph_vital_convert.dict");
+        for (String s:contentList) {
+            String[] splits = s.split("\\|");
+            vitalMap.put(splits[0],splits[1]);
         }
         return vitalMap;
     }

graph/src/main/resources/bolt.properties

@@ -5,14 +5,10 @@ pass_235 = diagbot@20180822
 
 # neo4j bolt credentials
 #\u7EBF\u4E0A\u4F7F\u7528
-bolt.uri=bolt://192.168.2.233
+bolt.uri=bolt://192.168.2.232
 bolt.user=neo4j
 bolt.passwd=root
 
-#\u533B\u5B66\u672F\u8BED\u4F7F\u7528
-bolt232.uri=bolt://192.168.2.232
-bolt232.user=neo4j
-bolt232.passwd=root
 
 #\u6D4B\u8BD5\u4F7F\u7528
 bolt112.uri=bolt://192.168.3.112

graph/src/main/resources/diagSort.dict

@@ -1,756 +0,0 @@
-BcX7V3pTwpetFaNdnKehnARlNLC4WkMM
-pFdZPuCKzszYU6xqspywv0pgEZ36UZf7
-cyrUnsE+xTu69RZQsnc3eg==
-wAG7h4jgsHxcX5zqNHHt/Q==
-FeneHV0jniUYclRR5n6EOK6TFu1St0Q+
-FeneHV0jniXhjOGBjP0tkYJ/8HhcFBMjQsjDFyh0etI=
-JXDJAOpdlPoQbzZMuyy9fQ==
-RnmiLlZn/N8QbzZMuyy9fQ==
-rh16PU/bLzkK6I86gb+Ao0pgEZ36UZf7
-7nUs+pzMGNQjLd5G+EcdiUpgEZ36UZf7
-2uRZ3LWgKU3RH5Nj+q+LtrATS+O+j2ux
-cn9SelEe5HuV5wTT88NyS0pgEZ36UZf7
-GYBI2zJwMBNey2dyHe3hZXRjEyS9gTVe
-ccapIA2Os+T9oXeA5vVZEUpgEZ36UZf7
-rlgWhYLTdSUKVV36DWVEmkpgEZ36UZf7
-gh+pwxxYTnu/GGpwIprIPQ==
-v90Q9YDK3e0QbzZMuyy9fQ==
-Thq2mIfRTdi8HjJqAapif66TFu1St0Q+
-9K+PZ38Hd/3Lq4u7hNFVk66TFu1St0Q+
-9K+PZ38Hd/0q17w2ajSKHK6TFu1St0Q+
-ZWQHTSD6hCtjsD7stN1IVkpgEZ36UZf7
-LZyp1gIf6wgpLJFGqVmt30pgEZ36UZf7
-9Mqch0gZ4bMvCICzkLDDGehZn9/adx3vvk9zQiFPShUQbzZMuyy9fQ==
-UCgJlS/HXezaY475fTCHFK6TFu1St0Q+
-UCgJlS/HXexHXYr3weuURK6TFu1St0Q+
-tlK7bfXVIBUQF98iypbgjkpgEZ36UZf7
-xbg5pYjlVtXGgDHUkbi1wK7QEgPGBpLdgymuBa+h7Sj5ddv1PS4NAA==
-ZBlMqkWFMgF4AoArZ/s7PQ==
-cbrTnbEyu0MQbzZMuyy9fQ==
-6950kamGyz1jn8atkAa4WS1kFUX8b1/V
-aZM1EQIbHX4QbzZMuyy9fQ==
-kdU8UcCILZA2zqe2dEz9kJTAjlN+0rCKQsjDFyh0etI=
-VuA+VaAbW6kQbzZMuyy9fQ==
-2xt2LoFXv4UQbzZMuyy9fQ==
-GeOoxHykR0NIkRc7oSI9s0DkVM7urTWs
-4fpWUFa+lAB8bnaDayw0F0pgEZ36UZf7
-PoSiDC1E8k0QbzZMuyy9fQ==
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-785EOhh4F5tf/w933Z8XSUpgEZ36UZf7
-O8LPxcSZWgDrtccsLlj5wA==
-MsAiyvZZGvKIR37fpmmVAUpgEZ36UZf7
-NUY6EzUNBcu69RZQsnc3eg==
-hIcKxvB0qrSIR37fpmmVAUpgEZ36UZf7
-hIcKxvB0qrQ1/obow+hNxNS3UCP+XxkeHMgLh0YjYP8QbzZMuyy9fQ==
-hIcKxvB0qrQ1/obow+hNxM87KOEe5EKOHMgLh0YjYP8QbzZMuyy9fQ==
-p+oXZGb9femkmRvSpkGJU0pgEZ36UZf7
-IgfkS/yzfiNl6qtXuMmmfa6TFu1St0Q+
-T8qiUcOxWGe69RZQsnc3eg==
-1suDit3Eq7XNgWyWzjfkBeK+1Ww6oK4tQsjDFyh0etI=
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-vdDujKxsGqSuYTcjFB8CYIW56gVH63DBT8qiUcOxWGe69RZQsnc3eg==
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-ocjyg6d/YZbcONVccNlNVA==
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graph/src/main/resources/lexicon.dict

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graph/src/test/java/org/diagbot/graph/CacheFile.java

@@ -6,19 +6,76 @@ import org.diagbot.pub.utils.security.EncrypDES;
 import java.io.FileWriter;
 import java.sql.Connection;
 import java.sql.ResultSet;
+import java.sql.SQLException;
 import java.sql.Statement;
+import java.util.*;
 
 public class CacheFile {
     public static void main(String[] args) {
         CacheFile cacheFile = new CacheFile();
-        cacheFile.diagSort();
-        cacheFile.sexAge();
-//        cacheFile.contentMaping();
-        cacheFile.vitalMaping();
+        cacheFile.diagClassifyMaping();
+
+    }
+    //疾病 -- 科室
+    public void diagDepartMaping(){
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            EncrypDES encrypDES = new EncrypDES();//加密对象
+            String path = this.getClass().getClassLoader().getResource("").getPath();
+            path = path.substring(0, path.indexOf("target"));
+            String sql = "SELECT k1.lib_name diag_name, k2.lib_name dept_name FROM kl_concept_common kcc, kl_concept k1, kl_concept k2 " +
+                    "where kcc.concept_id = k1.id and kcc.dept_id = k2.id " +
+                    "and k1.lib_type = 18 and kcc.dept_id  is not null";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            List<Map.Entry<String, String>> libaryList = rsToMap(rs, true);
+            FileWriter fw = new FileWriter(path + "src/main/resources/doc_result_mapping_diag.dict");
+            for (Map.Entry<String, String> entry : libaryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+        } catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
+    }
+    //疾病分类归一
+    public void diagClassifyMaping(){
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "lantone", "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8");
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            EncrypDES encrypDES = new EncrypDES();//加密对象
+            String path = this.getClass().getClassLoader().getResource("").getPath();
+            path = path.substring(0, path.indexOf("target"));
+            String sql = "SELECT g.diag_name,g.diag_bigName_classify,g.diag_subName_classify FROM `doc_bigsub_classify_diag` g ";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            FileWriter fw = new FileWriter(path + "src/main/resources/diagClassify.dict");
+            String  r1 ,r2,r3;
+            while (rs.next()) {
+                r1 = rs.getString(1);//本类名
+                r2 = rs.getString(2);//大类名
+                r3 = rs.getString(3);//小类名
+                fw.write(encrypDES.encrytor(r1+ "|" + r2+ "|" + r3));
+                fw.write("\n");
+            }
+            fw.close();
+        } catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
     }
     //诊断大小类对应
     public void diagSort(){
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "lantone", "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -46,7 +103,7 @@ public class CacheFile {
     }
     //诊断和性别,年龄的对应
     public void sexAge(){
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "lantone", "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -80,7 +137,7 @@ public class CacheFile {
 
     //标签类型对应
     public void contentMaping()  {
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "lantone", "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -108,7 +165,7 @@ public class CacheFile {
     }
     //体征及体征结果
     public void vitalMaping()  {
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "lantone", "jdbc:mysql://192.168.2.121:3306/med?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -123,7 +180,7 @@ public class CacheFile {
                     "\t`kl_relation` l \n" +
                     "\tLEFT JOIN kl_concept i1 ON l.start_id = i1.id \n" +
                     "\tLEFT JOIN kl_concept i2 ON l.end_id = i2.id \n" +
-                    "where l.relation_id=19 AND i1.lib_type=35 AND i2.lib_type=33 AND l.is_deleted='N'";
+                    "where l.relation_id=19 AND i1.lib_type=35 AND i2.lib_type=33";
             st = conn.createStatement();
             rs = st.executeQuery(sql);
             FileWriter fw = new FileWriter(path + "src/main/resources/vital.dict");
@@ -141,4 +198,28 @@ public class CacheFile {
             nlpJdbc.close(rs, st, conn);
         }
     }
+
+    private List<Map.Entry<String, String>> rsToMap(ResultSet rs, boolean isJoin) throws SQLException {
+        String r1 = "";
+        String r2 = "";
+        Map<String, String> libraryMap = new HashMap<>(10);
+        while (rs.next()) {
+            r1 = rs.getString(1);
+            r2 = rs.getString(2);
+            if (libraryMap.get(r1) == null) {
+                libraryMap.put(r1, r2);
+            } else if (isJoin && libraryMap.get(r1) != null) {
+                libraryMap.put(r1, libraryMap.get(r1) + "," + r2);
+            }
+        }
+
+        List<Map.Entry<String, String>> libraryList = new ArrayList<Map.Entry<String, String>>(libraryMap.entrySet());
+        Collections.sort(libraryList, new Comparator<Map.Entry<String, String>>() {
+            public int compare(Map.Entry<String, String> o1, Map.Entry<String, String> o2) {
+                return o1.getKey().compareTo(o2.getKey());
+            }
+        });
+
+        return libraryList;
+    }
 }

graphdb/src/main/java/org/diagbot/service/impl/KnowledgeServiceImpl.java

@@ -378,7 +378,7 @@ public class KnowledgeServiceImpl implements KnowledgeService {
     @Override
     public Map<String, List<FeatureRate>> getLisPacs(SearchData searchData) {
         String[] featureArray = StringUtils.split(searchData.getFeatureType(), ",");
-        List<String> featureList = Arrays.asList(featureArray);
+        List<String> featureList = Arrays.asList(searchData.getFeatureTypes());
         Map<String, List<FeatureRate>> lisPacsFeature = new HashMap<>();
         String webDiag = searchData.getDiag();
         List<String> webDiagList = null;

graphdb/src/main/resources/application.yml

@@ -6,14 +6,14 @@ spring:
     active: local
   data:
     neo4j:
-      uri: bolt://192.168.2.233:7687
+      uri: bolt://192.168.2.232:7687
       username: neo4j
       password: root
 
 # 驱动配置信息
   datasource:
     driver-class-name: org.neo4j.jdbc.Driver
-    url: jdbc:neo4j:http://192.168.2.233:7474
+    url: jdbc:neo4j:http://192.168.2.232:7474
     username: neo4j
     password: root
     #定义初始连接数

nlp/src/main/java/org/diagbot/nlp/feature/FeatureAnalyze.java

@@ -89,6 +89,10 @@ public class FeatureAnalyze {
                     } else {
                         l.setConcept(l.getConcept() + "," + NlpCache.standard_info_synonym_map.get(props[i]).get(l.getText()));
                     }
+                    //如果是症状或体征，进行标准术语转换
+                    if (props[i].equals(Constants.feature_type_symptom)) {
+                        l.setText(NlpCache.standard_info_synonym_map.get(props[i]).get(l.getText()));
+                    }
                 }
             }
         }

nlp/src/main/java/org/diagbot/nlp/feature/extract/CaseToken.java

@@ -100,16 +100,14 @@ public abstract class CaseToken {
             }
         }
         if (!hasFeature) {
-            if (sn < 5) {
-                Map<String, Object> fMap = new HashMap<>(10);
-                fMap.put("feature_name", lexeme.getText());
-                fMap.put("feature_type", featureType);
-                fMap.put("negative", key);
-                fMap.put("sn", String.valueOf(sn++));
-                fMap.put("property", lexeme.getProperty());
-                fMap.put("concept", lexeme.getConcept());
-                featuresList.add(fMap);
-            }
+            Map<String, Object> fMap = new HashMap<>(10);
+            fMap.put("feature_name", lexeme.getText());
+            fMap.put("feature_type", featureType);
+            fMap.put("negative", key);
+            fMap.put("sn", String.valueOf(sn++));
+            fMap.put("property", lexeme.getProperty());
+            fMap.put("concept", lexeme.getConcept());
+            featuresList.add(fMap);
         }
     }
 }

nlp/src/main/java/org/diagbot/nlp/feature/extract/CaseTokenTime.java

@@ -71,6 +71,9 @@ public class CaseTokenTime extends CaseToken {
 
                 if (time_value > 0) {
                     if ("年".equals(lexeme.getText()) || "年余".equals(lexeme.getText())) {
+                        if (time_value > 100) {
+                            time_value = 2018 - time_value;
+                        }
                         time_value = time_value * 365;
                     } else if ("月".equals(lexeme.getText()) || "月余".equals(lexeme.getText())) {
                         time_value = time_value * 30;

nlp/src/main/java/org/diagbot/nlp/participle/cfg/DefaultConfig.java

@@ -1,6 +1,7 @@
 package org.diagbot.nlp.participle.cfg;
 
 import org.diagbot.nlp.participle.word.Segment;
+import org.diagbot.pub.utils.PropertiesUtil;
 import org.diagbot.pub.utils.security.EncrypDES;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
@@ -22,6 +23,13 @@ public class DefaultConfig implements Configuration {
 
     Segment segment;
 
+    private String path_prefix = "";
+
+    public DefaultConfig() {
+        PropertiesUtil propertiesUtil = new PropertiesUtil("nlp.properties");
+        path_prefix = propertiesUtil.getProperty("cache.file.dir");
+    }
+
     public Segment loadMainDict(String path) {
         List<String> fileContents = readFileContents(path);
         logger.info("读取文件" + path + "结果：" + fileContents.size() + "行");
@@ -78,11 +86,15 @@ public class DefaultConfig implements Configuration {
     }
 
     public List<String> readFileContents(String path) {
+        if (!StringUtils.isEmpty(path_prefix)) path = path_prefix + path;
         InputStream is = null;
         List<String> fileContents = new ArrayList<String>(10);
         try {
             if (StringUtils.isEmpty(path)) path = DEFAULT_PATH;
             is = this.getClass().getClassLoader().getResourceAsStream(path);
+            File file = new File(path);
+//            File file = new File(this.getClass().getResource(path).getFile());
+            is = new FileInputStream(file);
             if (is == null) {
                 throw new RuntimeException(path + ".......文件未找到!!");
             }
@@ -117,6 +129,7 @@ public class DefaultConfig implements Configuration {
     }
 
     public void writeFileContents(List<String> contents, String path, String separator) {
+        if (!StringUtils.isEmpty(path_prefix)) path = path_prefix + path;
         try {
             FileWriter fw = new FileWriter(path);
             for (String content : contents) {

nlp/src/main/java/org/diagbot/nlp/util/NlpCache.java

@@ -31,12 +31,12 @@ public class NlpCache {
 
     public static void createSegmentCache() {
         Configuration configuration = new DefaultConfig();
-        segment_cache = configuration.loadMainDict("tc.dict");
+        segment_cache = configuration.loadMainDict( "tc.dict");
     }
 
     public static void createPushCache() {
         Configuration configuration = new DefaultConfig();
-        standard_info_push_map = configuration.loadMapDict("push-tc.dict");
+        standard_info_push_map = configuration.loadMapDict( "push-tc.dict");
     }
 
     public static void createSynonymCache() {
@@ -59,6 +59,7 @@ public class NlpCache {
 
     public static void createClassifyCache() {
         Configuration configuration = new DefaultConfig();
+
         standard_info_classify_map = configuration.loadMapDict("classify.dict");
     }
 

nlp/src/main/resources/chronic.dict

@@ -1 +0,0 @@
-kQHtQ28+jmR5grdNyynjjEpgEZ36UZf7

nlp/src/main/resources/nlp.properties

@@ -0,0 +1,3 @@
+#Êý¾ÝÎļþ´æ·Å·¾¶
+cache.file.dir=/opt/diagbot-push/cache_file/
+#cache.file.dir=d:\\cache_file\\

nlp/src/main/resources/relation.dict

@@ -1,79 +0,0 @@
-RNMak3cFWH4=
-ddolNu+ruoI=
-crSKo8ZJQWw=
-GLI7v4oJneU=
-z9odaTsZTe4=
-UtapbxnvICk=
-zCUYt/gJFTA=
-Zz6Ubw81PD0=
-yclD2AmKHJg=
-h4pBhb+B4Lk=
-8hKk85iZesU=
-0hgDIdsSBy4=
-rbTBQUekfEs=
-fxkh89TwKsc=
-ENBQhPq5htU=
-nK40VLls5Zw=
-hlUmDNbK6a4=
-rHRYnTdjAKA=
-5JujAdVP5E8=
-X2j2cnCysms=
-YEYDcVHi1BI=
-YLWWPYmlo7s=
-28BY78TjZOw=
-1zF5xvlmigE=
-5iH5AYe9ogQ=
-c1L+syscJqI=
-dCLIxiAaEPQ=
-nLmMNwLd9hU=
-KO6x8jrh1Go=
-PGU7FXe4EVw=
-Vt65EYLJtik=
-MowtsJaT+Eg=
-15XjiZKWWOQ=
-tvD9gnRGuE0=
-TS5FqQfA3Bo=
-8OTyr31+HZE=
-qdFv0AhEzho=
-W8g6uyvyhXY=
-33mX5o5YCuI=
-eN8E9yHmcuQ=
-Wrhyd5KGRwU=
-oXEQgo+FISY=
-In0GOQRAoNc=
-WeQ7RhGnT3E=
-izBKC43U5Do=
-yIxj3i9brYw=
-6/AAsiRaYHk=
-d6U7t3U9wHI=
-N6s43nxbRgM=
-o15aELxdA/0=
-csWORUAoN0g=
-IheffyTAFTQ=
-URoSRuJSqzQ=
-Hu0VMvGeJYM=
-qi/diuSUvPk=
-2lkFuZbZfSo=
-sVfatV4286o=
-JxjFv6u9Xg0=
-GHAXRYXi1X4=
-3PiS9MWTEcU=
-h0qS3XYvg7w=
-exAkRV4R8YY=
-VIiXu9Fzbfg=
-u6Lr+Jfr3PY=
-Slw/FnB9o4g=
-r7bymlovf1w=
-bSkSwBpuGHs=
-Xoa3vcFiseU=
-TXb4vMJd3ok=
-+XVC3EsH+pQ=
-J36KtM8/eqU=
-rc7iV++H97Y=
-itwdzE4pvKw=
-yuYZf2CANH0=
-2J2g4AT+OI4=
-cKsJV2K7OCI=
-yXcIkexvskc=
-W5cHtxiabQI=
-GDA1Yq67XoE=

public/src/main/java/org/diagbot/pub/jdbc/MysqlJdbc.java

@@ -131,6 +131,7 @@ public class MysqlJdbc {
             StringBuffer sb = new StringBuffer();
 
             int first_index = 0;
+            String val = "";
             for (int cursor = 0; cursor < data.size(); cursor ++) {
                 if (first_index > 0) {
                     sb.append(",");
@@ -142,7 +143,11 @@ public class MysqlJdbc {
                     }
                     if (data.get(cursor).get(columns[i]) != null) {
                         sb.append("'");
-                        sb.append(data.get(cursor).get(columns[i]));
+                        val = data.get(cursor).get(columns[i]).toString();
+                        if (val.indexOf("'") > -1) {
+                            val = val.replace("'", "\\'");
+                        }
+                        sb.append(val);
                         sb.append("'");
                     } else {
                         sb.append("''");
@@ -177,6 +182,7 @@ public class MysqlJdbc {
             conn.setAutoCommit(false);
             st = conn.createStatement();
             int batchIndex = 0;
+            String val = "";
             for (int cursor = 0; cursor < data.size(); cursor ++) {
                 String sql = joinInsetSql(table, columns);
                 sql += "(";
@@ -186,7 +192,11 @@ public class MysqlJdbc {
                     }
                     if (data.get(cursor).get(columns[i]) != null) {
                         sql += "'";
-                        sql += data.get(cursor).get(columns[i]);
+                        val = data.get(cursor).get(columns[i]).toString();
+                        if (val.indexOf("'") > -1) {
+                            val = val.replace("'", "\\'");
+                        }
+                        sql += val;
                         sql += "'";
                     } else {
                         sql += null;

push-web/pom.xml

@@ -49,6 +49,12 @@
 			<version>1.0.0</version>
 		</dependency>
 
+		<dependency>
+			<groupId>org.diagbot</groupId>
+			<artifactId>common-push</artifactId>
+			<version>1.0.0</version>
+		</dependency>
+
 		<dependency>
 			<groupId>org.diagbot</groupId>
 			<artifactId>bigdata-web</artifactId>

push-web/src/main/java/org/diagbot/push/config/InterceptorConfig.java

@@ -1,6 +1,7 @@
 package org.diagbot.push.config;
 
 import org.diagbot.bigdata.common.RegionInterceptor;
+import org.diagbot.common.push.cache.CacheFileManager;
 import org.springframework.context.annotation.Configuration;
 import org.springframework.web.servlet.config.annotation.InterceptorRegistration;
 import org.springframework.web.servlet.config.annotation.InterceptorRegistry;
@@ -20,5 +21,9 @@ public class InterceptorConfig implements WebMvcConfigurer {
         //登录拦截的管理器
         InterceptorRegistration registration = registry.addInterceptor(new RegionInterceptor());     //拦截的对象会进入这个类中进行判断
         registration.addPathPatterns("/**");                    //所有路径都被拦截
+
+        //生成数据文件
+        CacheFileManager cacheFileManager = new CacheFileManager();
+        cacheFileManager.createCacheFile();
     }
 }

push-web/src/main/java/org/diagbot/push/controller/AlgorithmController.java

@@ -6,6 +6,7 @@ import org.diagbot.common.javabean.Drugs;
 import org.diagbot.common.javabean.Filnlly;
 import org.diagbot.common.javabean.MedicalIndication;
 import org.diagbot.common.javabean.Medicition;
+import org.diagbot.common.push.filter.ClassifyDiag;
 import org.diagbot.common.work.FeatureRate;
 import org.diagbot.common.work.ResponseData;
 import org.diagbot.common.work.SearchData;
@@ -148,12 +149,10 @@ public class AlgorithmController extends BaseController {
             }
             List<FeatureRate> graphFeatureRates = graphResponseData.getDis();
             graphFeatureRates.addAll(disFeatureRates);
-            //把所有的诊断拿出来经过过滤层过滤
-            FilterSortDiag filterSortDiag = new FilterSortDiag();
-            List<FeatureRate> filterDiagList = filterSortDiag.filterDiag(graphResponseData, graphFeatureRates);
-            List<FeatureRate> filterSortDiagList = filterSortDiag.sortDiag(filterDiagList);
-            bigDataResponseData.setDis(filterSortDiagList);
+            bigDataResponseData.setDis(graphFeatureRates);
         }
+        //归一之前诊断信息
+        bigDataResponseData.setBeforeCombineDis(bigDataResponseData.getDis());
         //推送出的诊断信息作为参数传入知识图谱
         List<FeatureRate> pushDiags = new ArrayList<>();
         pushDiags.addAll(bigDataResponseData.getDis());
@@ -185,6 +184,13 @@ public class AlgorithmController extends BaseController {
         if(featureList.contains(Constants.feature_type_vital) && vitals.size() > 0){
             bigDataResponseData.setVitals(vitals);
         }
+
+        //把所有的诊断拿出来经过过滤层过滤
+        ClassifyDiag classifyDiag = new ClassifyDiag();
+        List<FeatureRate> upfes = classifyDiag.filterDiag(graphResponseData, pushDiags);
+        List<FeatureRate> classify = classifyDiag.diagClassify(upfes);
+        List<FeatureRate> featureRates = classifyDiag.sortDiag(classify);
+        bigDataResponseData.setDis(featureRates);
         response.setData(bigDataResponseData);
         return response;
     }

push-web/src/main/java/org/diagbot/push/controller/CacheFileManagerController.java

@@ -0,0 +1,48 @@
+package org.diagbot.push.controller;
+
+import org.diagbot.bigdata.common.ApplicationCacheUtil;
+import org.diagbot.common.push.cache.CacheFileManager;
+import org.diagbot.common.work.ResponseData;
+import org.diagbot.graph.util.CacheUtil;
+import org.diagbot.nlp.util.NlpCache;
+import org.diagbot.pub.api.Response;
+import org.diagbot.pub.web.BaseController;
+import org.springframework.stereotype.Controller;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.ResponseBody;
+
+import javax.servlet.http.HttpServletRequest;
+
+/**
+ * Created by louhr on 2019/8/16.
+ */
+@Controller
+@RequestMapping("/cache_file_manager")
+public class CacheFileManagerController extends BaseController {
+
+    @RequestMapping(value = "/create_file")
+    @ResponseBody
+    public Response<ResponseData> create(HttpServletRequest request) throws Exception {
+        Response<ResponseData> response = new Response<ResponseData>();
+        CacheFileManager cacheFileManager = new CacheFileManager();
+        cacheFileManager.createCacheFile();
+        //自然语言处理缓存更新
+        NlpCache.createSegmentCache();
+        NlpCache.createPushCache();
+        NlpCache.createClassifyCache();
+        NlpCache.createChronicCache();
+        NlpCache.createSynonymCache();
+        //更新图谱缓存
+        CacheUtil.createDiagSortCache();
+        CacheUtil.createSexAgeCache();
+        CacheUtil.createVitalCache();
+        CacheUtil.createDiagClassifyCache();
+        CacheUtil.createDiagClassifyJiCache();
+        CacheUtil.createDiagDepartCache();
+        //更新大数据缓存
+        ApplicationCacheUtil.createDoc_result_mapping_diag_map();
+        ApplicationCacheUtil.createDoc_result_mapping_filter_map();
+        ApplicationCacheUtil.createKl_result_mapping_standword_map();
+        return response;
+    }
+}

push-web/src/main/resources/static/dist/js/push.js

@@ -1,6 +1,6 @@
-var nlp_web_url = "http://223.93.170.82:5002/nlp-web";
-var bigdata_web_url = "http://192.168.2.186:5001/bigdata-web";
-var graph_web_url = "http://192.168.2.186:5003/graph-web";
+var nlp_web_url = "http://192.168.2.234:5002/nlp-web";
+var bigdata_web_url = "http://192.168.2.234:5001/bigdata-web";
+var graph_web_url = "http://192.168.2.234:5003/graph-web";
 // var push_web_url = "http://192.168.2.234:5008/push-web";
 
 // var nlp_web_url = "http://192.168.3.180:5002/nlp-web";

push-web/src/main/resources/static/pages/algorithm/list.html

@@ -181,6 +181,31 @@
                     <!-- /.box -->
                 </div>
 
+                <div class="col-xs-4">
+                    <div class="box">
+                        <div class="box-header">
+                            <h3 class="box-title">归一前诊断信息</h3>&nbsp;&nbsp;<label id="before_combine_participle_diag"></label>
+                        </div>
+                        <!-- /.box-header -->
+                        <div class="box-body">
+                            <table id="before_combine_diag_list" class="table table-bordered table-striped">
+                                <thead>
+                                <tr>
+                                    <th>diag</th>
+                                    <th>dept</th>
+                                    <th>rate</th>
+                                </tr>
+                                </thead>
+                                <tbody>
+
+                                </tbody>
+                            </table>
+                        </div>
+                        <!-- /.box-body -->
+                    </div>
+                    <!-- /.box -->
+                </div>
+
                 <div class="col-xs-4">
                     <div class="box">
                         <div class="box-header">
@@ -206,6 +231,14 @@
                 </div>
                 <!-- /.col -->
 
+
+
+
+
+            </div>
+            <!-- /.row -->
+
+            <div class="row">
                 <div class="col-xs-4">
                     <div class="box">
                         <div class="box-header">
@@ -231,12 +264,6 @@
                 </div>
                 <!-- /.col -->
 
-
-
-            </div>
-            <!-- /.row -->
-
-            <div class="row">
                 <div class="col-xs-4">
                     <div class="box">
                         <div class="box-header">
@@ -367,6 +394,7 @@
         var symptom = $("#symptom").val();
         if (diag != '' && symptom == '') {
             $('#diag_list').html("");
+            $('#before_combine_diag_list').html("");
             startDiag('/algorithm/page_neural', '#symptom_list', '1', resourceType, '111', '1');
             startDiag('/algorithm/page_neural', '#vital_list', '3,2,7', resourceType, '131', '3');
             startDiag('/algorithm/page_neural', '#lis_list', '4,2,7', resourceType, '141', '4');
@@ -379,6 +407,7 @@
             startDiag('/algorithm/page_neural', '#pacs_list', '5,2,7', resourceType, '51', '5');
 
             startDiagMapping('/algorithm/page_neural', '#diag_list', '2', resourceType, '21', '2');
+            startDiagMapping('/algorithm/page_neural', '#before_combine_diag_list', '2', resourceType, '21', '6');
         }
     }
 
@@ -485,7 +514,10 @@
                         $("#participle_pacs").html(json.data.participleSymptom);
                         json.data = json.data.pacs;
                     }
-
+                    if (tp == '6') {
+                        $("#before_combine_participle_diag").html(json.data.participleSymptom);
+                        json.data = json.data.beforeCombineDis;
+                    }
                     return json.data;
                 }
             }
@@ -601,7 +633,10 @@
                         $("#participle_pacs").html(json.data.participleSymptom);
                         json.data = json.data.pacs;
                     }
-
+                    if (tp == '6') {
+                        $("#before_combine_participle_diag").html(json.data.participleSymptom);
+                        json.data = json.data.beforeCombineDis;
+                    }
                     return json.data;
                 }
             }