Merge branch 'master' of http://118.31.7.2:3000/tzjy-code/digital_marketing into de'v

src/main/java/com/sztzjy/marketing/config/Constant.java

@@ -80,7 +80,7 @@ public class Constant {
     public static final String YHDLHYB = "用户登录活跃表";
     public static final String YHXFNLB  = "用户消费能力表";
     public static final String YHXWB = "用户行为表";
-    public static final String YHPLB = "用户评论表";
+    public static final String YHPLB = "用户商品评论数据";
 
 
     public static final String CONTEXT_OCR = "文章图片如下2024年我国发展改革领域\n" +

src/main/java/com/sztzjy/marketing/controller/stu/StuDigitalMarketingModelController.java

@@ -157,10 +157,15 @@ public class StuDigitalMarketingModelController {
     @AnonymousAccess
     public ResultEntity clusterAnalysisResult(@RequestBody ClusterScatterPlotDTO clusterScatterPlotDTO) {
 
+
         Integer t = clusterScatterPlotDTO.getT();
         Integer k = clusterScatterPlotDTO.getK();
         List<Map<String, Object>> deduplicatedDataList = clusterScatterPlotDTO.getDeduplicatedDataList();
 
+        if(k>deduplicatedDataList.size()){
+            return new ResultEntity(HttpStatus.ACCEPTED,"簇数K值不能大于数据条数");
+        }
+
         List<String> strings = convertToDelimitedStringList(deduplicatedDataList);
 
         //初始化数据
@@ -171,10 +176,10 @@ public class StuDigitalMarketingModelController {
         ArrayList<ArrayList<Float>> centerList = randomList(k, arrayLists);
 
         //开始迭代
-        ArrayList<ArrayList<ArrayList<Float>>> kmeans = kmeans(k, t, centerList);
+        KmeansDTO kmeansDTO = kmeans(k, t, centerList);
 
 
-        return new ResultEntity(HttpStatus.OK,kmeans);
+        return new ResultEntity(HttpStatus.OK,kmeansDTO);
     }
 
 

src/main/java/com/sztzjy/marketing/entity/dto/KmeansDTO.java

@@ -0,0 +1,17 @@
+package com.sztzjy.marketing.entity.dto;
+
+import lombok.Data;
+
+import java.util.ArrayList;
+
+/**
+ * @author tz
+ * @date 2024/8/28 9:09
+ */
+@Data
+public class KmeansDTO {
+
+    private ArrayList<ArrayList<ArrayList<Float>>> clusters;
+
+    private Integer iterations;
+}

src/main/java/com/sztzjy/marketing/service/impl/StuDigitalMarketingModelServiceImpl.java

@@ -158,9 +158,9 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
             // 创建词汇表
             Map<String, Integer> wordCount = new HashMap<>();
             // 读取停用词
-            Set<String> stopwords = this.loadStopwords("/usr/local/tianzeProject/digitalMarketing/jarAndDockerFile/停用词.txt");
+//            Set<String> stopwords = this.loadStopwords("/usr/local/tianzeProject/digitalMarketing/jarAndDockerFile/停用词.txt");
 
-//            Set<String> stopwords = this.loadStopwords("D:\\project\\digital_marketing\\src\\main\\resources\\停用词.txt");
+            Set<String> stopwords = this.loadStopwords("D:\\project\\digital_marketing\\src\\main\\resources\\words\\停用词.txt");
 
             // 统计词频
             int count = 0;
@@ -329,8 +329,6 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 //            list=indicatorsMapper.getYHXFNLB();
                 if(algorithmName.equals("关联规则挖掘")){
                     list.add("consumer_goods");
-                } else {
-                    list.add("id");
                 }
 
             }
@@ -393,7 +391,7 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
             table="stu_user_shopping_cart";
         }
 
-        else if(analyzeDataDTO.getTableName().equals(Constant.YHPLB)){ //查询用户评论
+        else if(analyzeDataDTO.getTableName().equals(Constant.YHPLB)){ //查询用户商品评论数据
             table="stu_user_comment";
 
         }else {

src/main/java/com/sztzjy/marketing/service/impl/UserBehaviorProfilingAnaServiceImpl.java

@@ -268,6 +268,10 @@ public class UserBehaviorProfilingAnaServiceImpl implements UserBehaviorProfilin
                 }
             }
 
+            if(count>100){
+                count=100;
+            }
+
             this.HashTrainingFractionalStatistics(userId, count, info);
         }
     }
@@ -611,6 +615,9 @@ public class UserBehaviorProfilingAnaServiceImpl implements UserBehaviorProfilin
             }
 
             if(stuScoreDetails.getLearningProjects().equals(Constant.SYBG_TCHMODULE)){
+                if(stuScoreDetails.getScoreProject()==null){
+                    stuScoreDetails.setScoreProject(0.0);
+                }
                 BigDecimal mul = bigDecimalUtils.mul(stuScoreDetails.getScoreProject().toString(), tchModuleWeight.getReportWeight().toString());
                 stuUser.setTestReportSocre(mul);
             }

src/main/java/com/sztzjy/marketing/util/algorithm/KMeansResult.java

@@ -1,5 +1,6 @@
 package com.sztzjy.marketing.util.algorithm;
 
+import com.sztzjy.marketing.entity.dto.KmeansDTO;
 import org.springframework.web.multipart.MultipartFile;
 
 import java.io.BufferedReader;
@@ -167,7 +168,7 @@ public class KMeansResult {
     }
 
     //最终聚类结果
-    public static ArrayList<ArrayList<ArrayList<Float>>> kmeans(int k,Integer t,ArrayList<ArrayList<Float>> centroids) {
+    public static KmeansDTO kmeans(int k, Integer t, ArrayList<ArrayList<Float>> centroids) {
         ArrayList<ArrayList<ArrayList<Float>>> clusters = new ArrayList<>(k);
         for (int i = 0; i < k; i++) {
             clusters.add(new ArrayList<>());
@@ -205,7 +206,11 @@ public class KMeansResult {
 //        for (int i = 0; i < k; i++) {
 //            System.out.println("簇 " + i + ": " + clusters.get(i));
 //        }
-        return clusters;
+
+        KmeansDTO kmeansDTO=new KmeansDTO();
+        kmeansDTO.setClusters(clusters);
+        kmeansDTO.setIterations(iterations);
+        return kmeansDTO;
     }
 
     //计算一个簇的质心

src/main/resources/mappers/StuTableNameMapper.xml

@@ -227,7 +227,7 @@
     <foreach collection="fieldList" item="field" separator=",">
       ${field}
     </foreach>
-    FROM ${table} where user_id=#{userId} and module=#{tableName} limit 0,1000
+    FROM ${table} where user_id=#{userId} and module=#{tableName} limit 0,100
   </select>