前言
公司项目涉及到员工任务管理，需要从员工任务中获取任务信息生成个人词云图，可以把员工任务中较为高频的词语突出展示。
一、词云是什么？
词云就是对文本中出现频率较高的“关键词”予以视觉上的突出，形成“关键词云层” 或“关键词渲染”，从而过滤掉大量的文本信息，使浏览网页者只要一眼扫过文本就可以领略文本的主旨。
二、使用步骤
1.引入依赖
<!-- IK分词器 -->
<dependency>
<groupId>cn.shenyanchao.ik-analyzer</groupId>
<artifactId>ik-analyzer</artifactId>
<version>9.0.0</version>
</dependency>
<!-- 詞雲 -->
<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>
<!-- web -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
2.application.yml
server:
port: 8088
# 关闭日志输出 （可选）
logging:
level:
com.kennycason.kumo.WordCloud: OFF
3.Controller
import com.chendi.mydemo.utils.IkAnalyzerUtils;
import com.chendi.mydemo.utils.WorkCloudUtil;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
@RestController
public class TestController {
@GetMapping("/")
public void test() {
List<String> list = new ArrayList<>();
list.add("爱购物，爱手机，爱电脑，爱上网");
list.add("爱学习，爱游戏，爱吃饭，爱睡觉");
list.add("爱上班，爱下班，爱加班，爱翘班");
list.add("爱上班，爱下班，爱加班，爱翘班");
list.add("夏天的阳光明媚灿烂，\n" +
"大自然万物生机盎然。\n" +
"清晨的微风吹过花丛，\n" +
"点缀着青草和蓝天。\n" +
"\n" +
"蝴蝶翩翩起舞在花间，\n" +
"蜜蜂忙碌采集甘甜。\n" +
"鸟儿欢快地歌唱着，\n" +
"为夏日带来欢欣和欢愉。\n" +
"\n" +
"海浪轻拍沙滩起伏，\n" +
"沙粒细腻温热宜走。\n" +
"阳光透过水面璀璨，\n" +
"让海洋如银河般流动。\n" +
"\n" +
"夏日的夜晚星空闪耀，\n" +
"月亮洒下银色光晕。\n" +
"夏虫的音符演奏着，\n" +
"营造出夏夜的美妙。\n" +
"\n" +
"夏天啊，你是如此迷人，\n" +
"给人们带来快乐和欢欣。\n" +
"在你的怀抱里，我们尽情享受，\n" +
"夏天，你是美丽的季节！");
Map<String, Integer> wordMap = IkAnalyzerUtils.wordCloud(list, 0);
WorkCloudUtil.generateWriteImage(wordMap);
}
}
4.分词工具类
import org.wltea.analyzer.core.IKSegmenter;
import org.wltea.analyzer.core.Lexeme;
import java.io.IOException;
import java.io.StringReader;
import java.util.*;
/**
* 解析工具类
*/
public class IkAnalyzerUtils {
/**
* 拆分词云
*
* @param list 需要拆分的词云集合
* @param quantity 结果集取的数量
*/
public static String wordCloudParsing(List<String> list, Integer quantity) {
Map<String,Integer> result = wordCloud(list,quantity);
StringBuilder str = new StringBuilder();
result.forEach((k, v) -> {
String value = " " + k;
str.append(value);
});
return str.toString().trim();
}
/**
* 拆分词云
*
* @param list 需要拆分的词云集合
* @param quantity 结果集取的数量
*/
public static List<Map<String,Object>> wordCloudList(List<String> list, Integer quantity) {
Map<String,Integer> result = wordCloud(list,quantity);
List<Map<String,Object>> mapList = new LinkedList<>();
result.forEach((k, v) -> {
Map<String,Object> map = new HashMap<>(16);
map.put("name",k);
map.put("value",v);
mapList.add(map);
});
Collections.reverse(mapList);
return mapList;
}
/**
* 拆分词云
*
* @param list 需要拆分的词云集合
* @param quantity 结果集取的数量
*/
public static Map<String,Integer> wordCloud(List<String> list, Integer quantity) {
StringReader reader = new StringReader(String.join(",", list));
IKSegmenter ikSegmenter = new IKSegmenter(reader, true);
Map<String, Integer> map = null;
try {
Lexeme lexeme;
map = new HashMap<>(16);
while ((lexeme = ikSegmenter.next()) != null) {
String str = lexeme.getLexemeText();
Integer num = map.get(str);
if (num != null && num > 0) {
map.put(str, num + 1);
} else {
map.put(str, 1);
}
}
reader.close();
} catch (IOException e) {
e.printStackTrace();
}
Map<String, Integer> result = new LinkedHashMap<>();
if (quantity != null && quantity > 0) {
map.entrySet().stream().sorted(Map.Entry.comparingByValue()).limit(quantity)
.forEachOrdered(item -> result.put(item.getKey(), item.getValue()));
} else {
map.entrySet().stream().sorted(Map.Entry.comparingByValue())
.forEachOrdered(item -> result.put(item.getKey(), item.getValue()));
}
return result;
}
}
4.词云生成工具类、支持输出文件和字节流
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.font.KumoFont;
import com.kennycason.kumo.font.scale.SqrtFontScalar;
import com.kennycason.kumo.nlp.FrequencyAnalyzer;
import com.kennycason.kumo.nlp.tokenizers.ChineseWordTokenizer;
import com.kennycason.kumo.palette.ColorPalette;
import lombok.SneakyThrows;
import java.awt.*;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
public class WorkCloudUtil {
@SneakyThrows
public static InputStream generateImageStream(Map<String, Integer> wordMap) {
WordCloud wordCloud = generateWordCloud(wordMap);
//输出字节流
ByteArrayOutputStream out =new ByteArrayOutputStream();
wordCloud.writeToStreamAsPNG(out);
return new ByteArrayInputStream(out.toByteArray());
}
@SneakyThrows
public static void generateWriteImage(Map<String, Integer> wordMap) {
WordCloud wordCloud = generateWordCloud(wordMap);
wordCloud.writeToFile("D:\\chendi\\cd.png");
}
public static WordCloud generateWordCloud(Map<String, Integer> wordMap){
if (wordMap == null || wordMap.size() == 0) {
return null;
}
final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(600);
frequencyAnalyzer.setMinWordLength(2);
frequencyAnalyzer.setWordTokenizer(new ChineseWordTokenizer());
final List<WordFrequency> wordFrequencies = new ArrayList<>();
for (Map.Entry<String, Integer> entry : wordMap.entrySet()) {
wordFrequencies.add(new WordFrequency(entry.getKey(), entry.getValue()));
}
Font font = FontUtil.getFont("/static/fonts/QingNiaoHuaGuangJianMeiHei-2.ttf");
//设置图片分辨率
final Dimension dimension = new Dimension(400, 400);
//此处的设置采用内置常量即可，生成词云对象
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
//设置边界及字体
wordCloud.setPadding(2);
wordCloud.setBackgroundColor(Color.WHITE);
//设置背景图层为圆形，设置圆形的大小
wordCloud.setBackground(new CircleBackground(200));
//设置词云显示的三种颜色，越靠前设置表示词频越高的词语的颜色
wordCloud.setColorPalette(new ColorPalette(new Color(0x4055F1), new Color(0x408DF1), new Color(0x40AAF1), new Color(0x40C5F1), new Color(0x40D3F1), new Color(0xFFFFFF)));
//设置字体的大小
wordCloud.setFontScalar(new SqrtFontScalar(10, 40));
wordCloud.setKumoFont(new KumoFont(font));
wordCloud.build(wordFrequencies);
//设置背景图片，如果想要固定的形状，就插入这个形状的图片
//wordCloud.setBackground(new PixelBoundryBackground("E:\\星星/star.jpg"));
return wordCloud;
}
}
注意
处理中文需要宿主机有中文字体包、如果宿主机不支持中文，请下载一个中文字体包
本文指定使用的就是QingNiaoHuaGuangJianMeiHei-2.ttf字体
百度一下、找不到私信我发你QingNiaoHuaGuangJianMeiHei-2.ttf字体包