完成词云生成任务

pom.xml

@@ -261,6 +261,18 @@
             <version>9.1.22</version>
         </dependency>
 
+<!--        //词云-->
+        <dependency>
+            <groupId>com.kennycason</groupId>
+            <artifactId>kumo-core</artifactId>
+            <version>1.28</version>
+        </dependency>
+        <dependency>
+            <groupId>com.kennycason</groupId>
+            <artifactId>kumo-tokenizers</artifactId>
+            <version>1.28</version>
+        </dependency>
+
     </dependencies>
 
     <build>

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

@@ -29,6 +29,7 @@ public class Constant {
     public static final String FILTEROUTSTATIS_TWO= "纳入";
     public static final String FILTEROUTSTATIS_THREE= "4";
     public static final String FILTEROUTSTATIS_FOUR= "2";
+    public static final String FILTEROUTSTATIS_fIVE_ON= "5";
     public static final String FILTEROUTSTATIS_FIVE= "5000";
     public static final String FILTEROUTSTATIS_SIX= "3";
     public static final String FILTEROUTSTATIS_SEVEN= "1000";

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

@@ -1,15 +1,19 @@
 package com.sztzjy.marketing.controller.stu;
 
+import cn.hutool.core.util.IdUtil;
+import cn.hutool.core.util.RandomUtil;
 import com.sztzjy.marketing.annotation.AnonymousAccess;
+import com.sztzjy.marketing.entity.dto.StuWordCreateDto;
+import com.sztzjy.marketing.util.TagWordCloudService;
 import com.sztzjy.marketing.util.file.IFileUtil;
 import io.swagger.annotations.Api;
 import io.swagger.annotations.ApiOperation;
 import org.springframework.beans.factory.annotation.Autowired;
-import org.springframework.web.bind.annotation.GetMapping;
-import org.springframework.web.bind.annotation.RequestMapping;
-import org.springframework.web.bind.annotation.RestController;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.web.bind.annotation.*;
 
 import javax.servlet.http.HttpServletResponse;
+import java.io.IOException;
 
 /**
  * @author 17803
@@ -25,6 +29,9 @@ public class DownloadDataController {
     @Autowired
     private IFileUtil iFileUtil;
 
+    @Value("${file.path}")
+    private String filePath;
+
 
     @AnonymousAccess
     @ApiOperation("RFM分析方法下载数据")
@@ -107,6 +114,22 @@ public class DownloadDataController {
     }
 
 
+    @AnonymousAccess
+    @ApiOperation("情感分析/文本挖掘词云生成")
+    @PostMapping("/wordCreateByAna")
+    public void wordCreateByAna(@RequestBody StuWordCreateDto stuWordCreateDto) throws IOException {
+
+        TagWordCloudService tagWordCloudService = new TagWordCloudService();
+
+        //1成图片路径，2.图云背景图片
+        String url =   filePath+"/word/" + IdUtil.simpleUUID()+"."+"png";
+
+
+        tagWordCloudService.generate(url,filePath+"/1.png",stuWordCreateDto.getContext());
+
+
+    }
+
 
 
 

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

@@ -50,6 +50,19 @@ public class UserBehaviorProfilingByRFM {
 
 
 
+    @AnonymousAccess
+    @ApiOperation("第四步:按价值打分")
+    @PostMapping("/scoreByValue")
+    public ResultEntity scoreByValue(@RequestBody StuMachineLearning stuMachineLearning) {
+
+        return userBehaviorProfilingByRFMService.scoreByValue(stuMachineLearning);
+
+    }
+
+
+
+
+
 
 
 }

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

@@ -0,0 +1,16 @@
+package com.sztzjy.marketing.entity.dto;
+
+import lombok.Data;
+
+/**
+ * @author 17803
+ * @date 2024-06-21 14:21
+ */
+
+@Data
+public class StuWordCreateDto {
+
+    private String context;
+    private String userId;
+
+}

src/main/java/com/sztzjy/marketing/service/UserBehaviorProfilingByRfmService.java

@@ -23,4 +23,12 @@ public interface UserBehaviorProfilingByRfmService {
     */
 
     ResultEntity calculateRfm(StuMachineLearning stuMachineLearning);
+
+    /**
+        * 按价值打分
+        * @param stuMachineLearning
+        * @return
+    */
+
+    ResultEntity scoreByValue(StuMachineLearning stuMachineLearning);
 }

src/main/java/com/sztzjy/marketing/service/UserBehaviorProfilingByRfmServiceImpl.java

@@ -105,6 +105,15 @@ public class UserBehaviorProfilingByRfmServiceImpl implements UserBehaviorProfil
         //判断结果是否正确
         StuBehaviorProfilingDTO behaviorProfilingDTO = checkAnswerByTwoSub(learning);
 
+
+        return     selectRfmInfo(learning,behaviorProfilingDTO);
+
+    }
+
+
+
+
+    private ResultEntity selectRfmInfo(StuMachineLearning learning, StuBehaviorProfilingDTO behaviorProfilingDTO) {
         //查询是否提交，已提交不做任何修改，未提交校验结果并保存，修改对应提交状态
 
         StuMachineLearningExample machineLearningExample = new StuMachineLearningExample();
@@ -153,10 +162,100 @@ public class UserBehaviorProfilingByRfmServiceImpl implements UserBehaviorProfil
         }
     }
 
+    /**
+        * 第四步:按价值打分
+        * @param stuMachineLearning
+        * @return
+    */
+
+    @Override
+    public ResultEntity scoreByValue(StuMachineLearning stuMachineLearning) {
+
+
+        //判断结果是否正确
+        StuBehaviorProfilingDTO behaviorProfilingDTO = checkAnswerByFourSub(stuMachineLearning);
+
+        //同意查询用户数据
+        return     selectRfmInfo(stuMachineLearning,behaviorProfilingDTO);
+    }
+
+    private StuBehaviorProfilingDTO checkAnswerByFourSub(StuMachineLearning learning) {
+        //用来存储错误字段和正确答案
+        // 使用 fastjson 将 JSON 字符串转换回 Map
+        Map<String, String> map = JSON.parseObject(learning.getErrorField(), HashMap.class);
+
+
+        //错误次数
+        int count = 0;
+
+
+        if (!Constant.FILTEROUTSTATIS_THREE.equals(learning.getStepFiveB())){
+            count ++;
+
+            map.put("stepFiveB",Constant.FILTEROUTSTATIS_THREE);
+        }
+
+        if (!Constant.FILTEROUTSTATIS_FOUR.equals(learning.getStepFiveC())){
+            count ++;
+            map.put("stepFiveC",Constant.FILTEROUTSTATIS_FOUR);
 
+        }
+
+        if (!Constant.FILTEROUTSTATIS_THREE.equals(learning.getStepFiveD())){
+            count ++;
+            map.put("stepFiveD",Constant.FILTEROUTSTATIS_THREE);
+        }
 
 
 
+        if (!Constant.FILTEROUTSTATIS_fIVE_ON.equals(learning.getStepSixA())){
+            count ++;
+            map.put("stepSixA",Constant.FILTEROUTSTATIS_fIVE_ON);
+        }
+
+        if (!Constant.FILTEROUTSTATIS_FOUR.equals(learning.getStepSixB())){
+            count ++;
+            map.put("stepSixB",Constant.FILTEROUTSTATIS_FOUR);
+        }
+
+        if (!Constant.FILTEROUTSTATIS_FOUR.equals(learning.getStepSixC())){
+            count ++;
+            map.put("stepSixC",Constant.FILTEROUTSTATIS_FOUR);
+        }
+
+
+
+
+        if (!Constant.FILTEROUTSTATIS_fIVE_ON.equals(learning.getStepSixD())){
+            count ++;
+            map.put("stepSixD",Constant.FILTEROUTSTATIS_fIVE_ON);
+        }
+        if (!Constant.FILTEROUTSTATIS_EIGHT.equals(learning.getStepSevenA())){
+            count ++;
+            map.put("stepSevenA",Constant.FILTEROUTSTATIS_EIGHT);
+        }
+        if (!Constant.FILTEROUTSTATIS_EIGHT.equals(learning.getStepSevenB())){
+            count ++;
+            map.put("stepSevenB",Constant.FILTEROUTSTATIS_EIGHT);
+        }
+
+
+        Integer number = 9 - count;
+
+        //获取上一次得分
+
+        Integer sum =  learning.getSuccessNumber() + number;
+
+
+        //拼接上一次错误字段
+        learning.getErrorField();
+
+
+        StuBehaviorProfilingDTO stuBehaviorProfilingDTO = StuBehaviorProfilingDTO.builder().map(map).count(sum).build();
+
+        return stuBehaviorProfilingDTO;
+
+    }
 
 
     //第一步:筛选出统计样本结果校验

src/main/java/com/sztzjy/marketing/util/TagWordCloudService.java

@@ -0,0 +1,114 @@
+package com.sztzjy.marketing.util;
+
+import com.kennycason.kumo.CollisionMode;
+import com.kennycason.kumo.WordCloud;
+import com.kennycason.kumo.WordFrequency;
+import com.kennycason.kumo.bg.CircleBackground;
+import com.kennycason.kumo.bg.PixelBoundaryBackground;
+import com.kennycason.kumo.font.KumoFont;
+import com.kennycason.kumo.font.scale.SqrtFontScalar;
+import com.kennycason.kumo.image.AngleGenerator;
+import com.kennycason.kumo.nlp.FrequencyAnalyzer;
+import com.kennycason.kumo.nlp.tokenizers.ChineseWordTokenizer;
+import com.kennycason.kumo.palette.ColorPalette;
+
+import java.awt.*;
+import java.io.ByteArrayInputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+
+import static cn.hutool.core.io.FileUtil.getInputStream;
+
+public class TagWordCloudService {
+
+    // 照片纵横比
+    private double ratio = 1;
+    // 获取词云图片
+    // wordFile：单词及其频率文件路径
+    // pngOutputPath：图片输出路径，应该以.png结尾
+    // shapePicPath：词云形状图片路径，其背景应为透明背景，格式为png
+    public void generate(String pngOutputPath, String shapePicPath,String context) throws IOException {
+//        final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
+        // 共检索多少个词
+//        frequencyAnalyzer.setWordFrequenciesToReturn(1000);
+        // 单词最短长度，一个汉字和一个英文字符都是1
+//        frequencyAnalyzer.setMinWordLength(2);
+//        frequencyAnalyzer.setStopWords(loadStopWords());
+        // 设置中文支持，另一种加载方式不用设置
+//        frequencyAnalyzer.setWordTokenizer(new ChineseWordTokenizer());
+//        final List<WordFrequency> wordFrequencies;
+//        // 加载词云有两种方式，一种是在txt文件中统计词出现的个数，另一种是直接给出每个词出现的次数，这里使用第二种
+//        // 文件格式如下
+////        100: frog
+////        94: dog
+////        43: cog
+////        20: bog
+//        FrequencyFileLoader frequencyFileLoader = new FrequencyFileLoader();
+//        File file = new File(wordFile);
+//        wordFrequencies = frequencyFileLoader.load(file);
+        // 可以直接从文件中读取
+        FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
+        frequencyAnalyzer.setWordFrequenciesToReturn(600);
+        frequencyAnalyzer.setMinWordLength(2);
+        frequencyAnalyzer.setWordTokenizer(new ChineseWordTokenizer());
+        InputStream inputStream = null;
+        List<WordFrequency> wordFrequencies = null;
+
+        try  {
+            inputStream = new ByteArrayInputStream(context.getBytes(StandardCharsets.UTF_8));
+             wordFrequencies = frequencyAnalyzer.load(inputStream);
+
+        }catch (Exception e) {
+            e.printStackTrace();
+        }finally {
+            if (inputStream != null) {
+                try {
+                    inputStream.close();
+                } catch (Exception e) {
+                    e.printStackTrace();
+                }
+            }
+        }
+
+//        final Dimension dimension = new Dimension(600, 600);
+//        final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
+//        wordCloud.setPadding(2);
+//        wordCloud.setBackground(new CircleBackground(300));
+       // wordCloud.setColorPalette(new ColorPalette(new Color(0x4055F1), new Color(0x408DF1), new Color(0x40AAF1), new Color(0x40C5F1), new Color(0x40D3F1), new Color(0xFFFFFF)));
+//        wordCloud.setFontScalar(new SqrtFontScalar(10, 40));
+
+
+        // 生成图片的像素大小
+        //设置图片分辨率
+        Dimension dimension = new Dimension(600, 600);
+//        final Dimension dimension = new Dimension(1024, (int)(1024*ratio));
+        final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
+        // 调节词云的稀疏程度，越高越稀疏
+        wordCloud.setPadding(2);
+
+//        //设置背景色
+        wordCloud.setBackgroundColor(new Color(255,255,255));
+        //设置背景图片
+        //wordCloud.setBackground(new PixelBoundaryBackground(shapePicPath));
+//        wordCloud.setBackground(new CircleBackground(300));
+        wordCloud.setBackground(new CircleBackground(300));
+
+        // 颜色模板，不同频率的颜色会不同
+       wordCloud.setColorPalette(new ColorPalette(new Color(0x4055F1), new Color(0x408DF1), new Color(0x40AAF1), new Color(0x40C5F1), new Color(0x40D3F1), new Color(0xFFFFFF)));
+        // 设置字体
+        Font font = new Font("楷体", 0, 25);
+        wordCloud.setKumoFont(new KumoFont(font));
+        // 设置偏转角，角度为0时，字体都是水平的
+//        wordCloud.setAngleGenerator(new AngleGenerator(0, 90, 9));
+        wordCloud.setAngleGenerator(new AngleGenerator(0));
+        // 字体的大小范围，最小是多少，最大是多少
+        wordCloud.setFontScalar(new SqrtFontScalar(10, 40));
+
+        wordCloud.build(wordFrequencies);
+        wordCloud.writeToFile(pngOutputPath);
+
+
+    }
+}