Merge remote-tracking branch 'origin/master'

# Conflicts:
#	src/main/java/com/github/houbb/sensitive/word/support/check/WordCheckWord.java

CHANGE_LOG.md

@@ -414,9 +414,8 @@
 | 1  | A    | wordCheck 策略支持用户自定义  | 2025-2-17 12:06:45 | https://github.com/houbb/sensitive-word/issues/101 |
 | 2  | A    | wordCheckUrlNoPrefix | 2025-2-17 12:06:45 | https://github.com/houbb/sensitive-word/issues/101 |
 
-# release_0.25.0
+# release_0.25.1
 
-| 序号 | 变更类型 | 说明                   | 时间                 | 备注   |
+| 序号 | 变更类型 | 说明                           | 时间                | 备注                                                 |
-|:---|:-----|----------------------|:-------------------|:-----|
+|:---|:-----|------------------------------|:------------------|:---------------------------------------------------|
-| 1  | A    | wordCheck 策略支持用户自定义  | 2025-2-17 12:06:45 | https://github.com/houbb/sensitive-word/issues/101 |
+| 1  | A    | 修正 tags 匹配问题，黑名单命中时返回对应的黑名单词 | 2025-5-2 20:25:04 | https://github.com/houbb/sensitive-word/issues/105 |
-| 2  | A    | wordCheckUrlNoPrefix | 2025-2-17 12:06:45 | https://github.com/houbb/sensitive-word/issues/101 |

README.md

@@ -96,7 +96,7 @@ v0.24.0 开始内置支持对敏感词的分类细化，不过工作量比较大
 <dependency>
     <groupId>com.github.houbb</groupId>
     <artifactId>sensitive-word</artifactId>
-    <version>0.25.0</version>
+    <version>0.25.1</version>
 </dependency>
 ```
 
@@ -1289,6 +1289,14 @@ FormatCombine/CheckCombine/AllowDenyCombine 组合策略，允许用户自定义
 
 [v0.21.0 敏感词新特性之白名单支持单个编辑，修正白名单包含黑名单时的问题](https://houbb.github.io/2020/01/07/sensitive-word-12-v0.21.0-allow-word-edit)
 
+[v0.23.0 敏感词结果条件拓展，内置支持链式+单词标签](https://houbb.github.io/2020/01/07/sensitive-word-13-v0.23.0-result-condition-enhance)
+
+[v0.24.0 新特性支持标签分类，内置实现多种策略](https://houbb.github.io/2020/01/07/sensitive-word-13-v0.24.0-word-tag-impl)
+
+[v0.25.0 新特性之 wordCheck 策略支持用户自定义](https://houbb.github.io/2020/01/07/sensitive-word-14-v0.25.0-url-define)
+
+[v0.25.1 新特性之返回匹配词，修正 tags 标签](https://houbb.github.io/2020/01/07/sensitive-word-14-v0.25.1-tags-match)
+
 ![wechat](https://img-blog.csdnimg.cn/63926529df364f09bcb203a8a9016854.png)
 
 # NLP 开源矩阵

pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.github.houbb</groupId>
     <artifactId>sensitive-word</artifactId>
-    <version>0.25.0</version>
+    <version>0.25.1</version>
 
     <properties>
         <!--============================== All Plugins START ==============================-->

release.bat

@@ -10,7 +10,7 @@ ECHO "============================= RELEASE START..."
 
 :: 版本号信息(需要手动指定)
 :::: 旧版本名称
-SET version=0.25.0
+SET version=0.25.1
 :::: 新版本名称
 SET newVersion=0.26.0
 :::: 组织名称

src/main/java/com/github/houbb/sensitive/word/api/IWordResult.java

@@ -28,4 +28,11 @@ public interface IWordResult {
      */
     String type();
 
+    /**
+     * 实际匹配的单词，方便统一的标签等处理，实际问题排查等
+     * @return 结果
+     * @since 0.25.1
+     */
+    String word();
+
 }

src/main/java/com/github/houbb/sensitive/word/core/SensitiveWord.java

@@ -6,6 +6,7 @@ import com.github.houbb.sensitive.word.api.*;
 import com.github.houbb.sensitive.word.api.context.InnerSensitiveWordContext;
 import com.github.houbb.sensitive.word.constant.enums.WordValidModeEnum;
 import com.github.houbb.sensitive.word.support.check.WordCheckResult;
+import com.github.houbb.sensitive.word.support.result.WordLengthResult;
 import com.github.houbb.sensitive.word.support.result.WordResult;
 import com.github.houbb.sensitive.word.utils.InnerWordFormatUtils;
 
@@ -80,13 +81,16 @@ public class SensitiveWord extends AbstractSensitiveWord {
 
 
             // 命中
-            int wordLength = checkResult.wordLengthResult().wordDenyLen();
+            final WordLengthResult wordLengthResult = checkResult.wordLengthResult();
+            int wordLength = wordLengthResult.wordDenyLen();
             if (wordLength > 0) {
                 // 保存敏感词
                 WordResult wordResult = WordResult.newInstance()
                         .startIndex(i)
                         .endIndex(i+wordLength)
-                        .type(checkResult.type());
+                        .type(checkResult.type())
+                        .word(wordLengthResult.wordDeny());
+
                 //v0.13.0 添加判断
                 if(wordResultCondition.match(wordResult, text, modeEnum, context)) {
                     resultList.add(wordResult);

src/main/java/com/github/houbb/sensitive/word/support/check/AbstractWordCheck.java

@@ -59,7 +59,8 @@ public abstract class AbstractWordCheck implements IWordCheck {
         return WordCheckResult.newInstance()
                 .wordLengthResult(wordLengthResult)
                 .type(getType())
-                .checkClass(clazz);
+                .checkClass(clazz)
+                ;
     }
 
 }

src/main/java/com/github/houbb/sensitive/word/support/result/WordLengthResult.java

@@ -15,6 +15,18 @@ public class WordLengthResult {
      */
     private int wordDenyLen;
 
+    /**
+     * 黑名单匹配词
+     * @since 0.25.1
+     */
+    private String wordDeny;
+
+    /**
+     * 白名单实际匹配值
+     * @since 0.25.1
+     */
+    private String wordAllow;
+
     public static WordLengthResult newInstance() {
         return new WordLengthResult();
     }
@@ -37,11 +49,31 @@ public class WordLengthResult {
         return this;
     }
 
+    public String wordDeny() {
+        return wordDeny;
+    }
+
+    public WordLengthResult wordDeny(String wordDeny) {
+        this.wordDeny = wordDeny;
+        return this;
+    }
+
+    public String wordAllow() {
+        return wordAllow;
+    }
+
+    public WordLengthResult wordAllow(String wordAllow) {
+        this.wordAllow = wordAllow;
+        return this;
+    }
+
     @Override
     public String toString() {
         return "WordLengthResult{" +
                 "wordAllowLen=" + wordAllowLen +
                 ", wordDenyLen=" + wordDenyLen +
+                ", wordDeny='" + wordDeny + '\'' +
+                ", wordAllow='" + wordAllow + '\'' +
                 '}';
     }
 

src/main/java/com/github/houbb/sensitive/word/support/result/WordResult.java

@@ -18,6 +18,12 @@ public class WordResult implements IWordResult {
      */
     private String type;
 
+    /**
+     * 单词匹配
+     * @since 0.25.0
+     */
+    private String word;
+
     private WordResult(){}
 
     public static WordResult newInstance() {
@@ -54,12 +60,23 @@ public class WordResult implements IWordResult {
         return this;
     }
 
+    @Override
+    public String word() {
+        return word;
+    }
+
+    public WordResult word(String word) {
+        this.word = word;
+        return this;
+    }
+
     @Override
     public String toString() {
         return "WordResult{" +
                 "startIndex=" + startIndex +
                 ", endIndex=" + endIndex +
                 ", type='" + type + '\'' +
+                ", word='" + word + '\'' +
                 '}';
     }
 

src/main/java/com/github/houbb/sensitive/word/support/result/WordResultHandlerWordTags.java

@@ -1,5 +1,6 @@
 package com.github.houbb.sensitive.word.support.result;
 
+import com.github.houbb.heaven.util.util.CollectionUtil;
 import com.github.houbb.sensitive.word.api.IWordContext;
 import com.github.houbb.sensitive.word.api.IWordResult;
 import com.github.houbb.sensitive.word.utils.InnerWordCharUtils;
@@ -17,15 +18,22 @@ public class WordResultHandlerWordTags extends AbstractWordResultHandler<WordTag
 
     @Override
     protected WordTagsDto doHandle(IWordResult wordResult, IWordContext wordContext, String originalText) {
+        WordTagsDto dto = new WordTagsDto();
+
         // 截取
         String word = InnerWordCharUtils.getString(originalText.toCharArray(), wordResult);
-        // 标签
 
-        WordTagsDto dto = new WordTagsDto();
+        // 获取 tags (使用清理后的单词查找标签)
-        dto.setWord(word);
-        // 获取 tags
         Set<String> wordTags = InnerWordTagUtils.tags(word, wordContext);
+
+        // 如果为空，则尝试使用命中的敏感词匹配 v0.25.1 bug105
+        if(CollectionUtil.isEmpty(wordTags)) {
+            wordTags = InnerWordTagUtils.tags(wordResult.word(), wordContext);
+        }
+
+        dto.setWord(word);
         dto.setTags(wordTags);
+
         return dto;
     }
 

src/main/java/com/github/houbb/sensitive/word/utils/InnerWordTagUtils.java

@@ -26,7 +26,7 @@ public class InnerWordTagUtils {
     public static Set<String> tags(final String word,
                             final IWordContext wordContext) {
         if(StringUtil.isEmpty(word)) {
-            return Collections.emptySet();
+            return null;
         }
 
         final IWordTag wordTag = wordContext.wordTag();

src/test/java/com/github/houbb/sensitive/word/bugs/b105/Bug105Test.java

@@ -0,0 +1,88 @@
+package com.github.houbb.sensitive.word.bugs.b105;
+
+import java.util.*;
+
+import com.github.houbb.heaven.util.util.CollectionUtil;
+import org.junit.Assert;
+import org.junit.Test;
+
+import com.github.houbb.sensitive.word.bs.SensitiveWordBs;
+import com.github.houbb.sensitive.word.support.ignore.SensitiveWordCharIgnores;
+import com.github.houbb.sensitive.word.support.result.WordResultHandlers;
+import com.github.houbb.sensitive.word.support.result.WordTagsDto;
+import com.github.houbb.sensitive.word.support.tag.WordTags;
+
+/**
+ * 测试Issue #105: 处理带有噪音字符时的标签查找
+ * 验证在启用字符忽略功能时，敏感词标签仍能被正确查找
+ *
+ * src/main/java/com/github/houbb/sensitive/word/support/result/WordResultHandlerWordTags.java
+ * @since 0.25.1
+ */
+public class Bug105Test {
+
+        @Test
+        public void testNoiseCharacterInTaggedWords() {
+                Map<String, Set<String>> newHashMap = new HashMap<>();
+                newHashMap.put("毛主席", new HashSet<>(Arrays.asList("政治", "领导人")));
+
+                // 配置同时启用字符忽略和标签的实例
+                SensitiveWordBs ignoreAndTagWordBs = SensitiveWordBs.newInstance()
+                                .charIgnore(SensitiveWordCharIgnores.specialChars()) // 启用字符忽略
+                                .wordTag(WordTags.map(newHashMap))
+                                .init();
+
+                // 包含噪音字符的敏感词文本
+                final String noisyText = "你好毛---主---席";
+
+                // 测试同时启用字符忽略和标签的实例（修复前会失败）
+                List<WordTagsDto> fixedWord = ignoreAndTagWordBs.findAll(noisyText, WordResultHandlers.wordTags());
+                Assert.assertEquals(1, fixedWord.size());
+                Assert.assertEquals("毛---主---席", fixedWord.get(0).getWord());
+                Assert.assertNotNull("标签不应为空", fixedWord.get(0).getTags());
+                Assert.assertTrue("应包含'政治'标签", fixedWord.get(0).getTags().contains("政治"));
+                Assert.assertTrue("应包含'领导人'标签", fixedWord.get(0).getTags().contains("领导人"));
+        }
+
+        @Test
+        public void testNoiseCharacterInTaggedWords2() {
+                Map<String, Set<String>> newHashMap = new HashMap<>();
+                newHashMap.put("毛主席", new HashSet<>(Arrays.asList("政治", "领导人")));
+                newHashMap.put("毛---主---席", new HashSet<>(Arrays.asList("政治", "领导人", "自定义的")));
+
+                // 配置同时启用字符忽略和标签的实例
+                SensitiveWordBs ignoreAndTagWordBs = SensitiveWordBs.newInstance()
+                        .charIgnore(SensitiveWordCharIgnores.specialChars()) // 启用字符忽略
+                        .wordTag(WordTags.map(newHashMap))
+                        .init();
+
+                // 包含噪音字符的敏感词文本
+                final String noisyText = "你好毛---主---席";
+
+                // 测试同时启用字符忽略和标签的实例（修复前会失败）
+                List<WordTagsDto> fixedWord = ignoreAndTagWordBs.findAll(noisyText, WordResultHandlers.wordTags());
+                Assert.assertEquals(1, fixedWord.size());
+                Assert.assertEquals("[政治, 自定义的, 领导人]", fixedWord.get(0).getTags().toString());
+        }
+
+        @Test
+        public void testNoiseCharacterInTaggedWords3() {
+                Map<String, Set<String>> newHashMap = new HashMap<>();
+                newHashMap.put("毛xxx主xxxx席", new HashSet<>(Arrays.asList("政治", "领导人", "自定义的")));
+
+                // 配置同时启用字符忽略和标签的实例
+                SensitiveWordBs ignoreAndTagWordBs = SensitiveWordBs.newInstance()
+                        .charIgnore(SensitiveWordCharIgnores.specialChars()) // 启用字符忽略
+                        .wordTag(WordTags.map(newHashMap))
+                        .init();
+
+                // 包含噪音字符的敏感词文本
+                final String noisyText = "你好毛---主---席";
+
+                // 测试同时启用字符忽略和标签的实例（修复前会失败）
+                List<WordTagsDto> fixedWord = ignoreAndTagWordBs.findAll(noisyText, WordResultHandlers.wordTags());
+                Assert.assertEquals(1, fixedWord.size());
+                Assert.assertTrue(CollectionUtil.isEmpty(fixedWord.get(0).getTags()));
+        }
+
+}

src/test/java/com/github/houbb/sensitive/word/core/SensitiveWordHelperTest.java

@@ -62,7 +62,7 @@ public class SensitiveWordHelperTest {
         final String text = "五星红旗迎风飘扬，毛主席的画像屹立在天安门前。";
 
         List<IWordResult> wordList = SensitiveWordHelper.findAll(text, WordResultHandlers.raw());
-        Assert.assertEquals("[WordResult{startIndex=0, endIndex=4, type='WORD'}, WordResult{startIndex=9, endIndex=12, type='WORD'}, WordResult{startIndex=18, endIndex=21, type='WORD'}]", wordList.toString());
+        Assert.assertEquals("[WordResult{startIndex=0, endIndex=4, type='WORD', word='5星红旗'}, WordResult{startIndex=9, endIndex=12, type='WORD', word='毛主席'}, WordResult{startIndex=18, endIndex=21, type='WORD', word='天安门'}]", wordList.toString());
     }
 
 
@@ -99,7 +99,7 @@ public class SensitiveWordHelperTest {
         final String text = "五星红旗迎风飘扬，毛主席的画像屹立在天安门前。";
 
         IWordResult word = SensitiveWordHelper.findFirst(text, WordResultHandlers.raw());
-        Assert.assertEquals("WordResult{startIndex=0, endIndex=4, type='WORD'}", word.toString());
+        Assert.assertEquals("WordResult{startIndex=0, endIndex=4, type='WORD', word='5星红旗'}", word.toString());
     }
 
     /**

src/test/java/com/github/houbb/sensitive/word/support/handler/WordResultHandlerTest.java

@@ -10,7 +10,7 @@ import org.junit.Assert;
 import org.junit.Ignore;
 import org.junit.Test;
 
-import java.util.List;
+import java.util.*;
 
 /**
  * @since 0.12.0
@@ -27,7 +27,7 @@ public class WordResultHandlerTest {
         Assert.assertEquals("[五星红旗, 毛主席, 天安门]", wordList2.toString());
 
         List<IWordResult> wordList3 = SensitiveWordHelper.findAll(text, WordResultHandlers.raw());
-        Assert.assertEquals("[WordResult{startIndex=0, endIndex=4, type='WORD'}, WordResult{startIndex=9, endIndex=12, type='WORD'}, WordResult{startIndex=18, endIndex=21, type='WORD'}]", wordList3.toString());
+        Assert.assertEquals("[WordResult{startIndex=0, endIndex=4, type='WORD', word='5星红旗'}, WordResult{startIndex=9, endIndex=12, type='WORD', word='毛主席'}, WordResult{startIndex=18, endIndex=21, type='WORD', word='天安门'}]", wordList3.toString());
     }
 
     @Test
@@ -35,20 +35,24 @@ public class WordResultHandlerTest {
         final String text = "骂人：你他妈; 邮箱：123@qq.com; mobile: 13088889999; 网址：https://www.baidu.com";
         List<IWordResult> wordList3 = SensitiveWordHelper
                 .findAll(text, WordResultHandlers.raw());
-        Assert.assertEquals("[WordResult{startIndex=3, endIndex=6, type='WORD'}]", wordList3.toString());
+        Assert.assertEquals("[WordResult{startIndex=3, endIndex=6, type='WORD', word='你他妈'}]", wordList3.toString());
     }
 
     @Test
-    @Ignore
     public void wordTagsTest() {
         final String text = "五星红旗迎风飘扬，毛主席的画像屹立在天安门前。";
 
         // 默认敏感词标签为空
         List<WordTagsDto> wordList1 = SensitiveWordHelper.findAll(text, WordResultHandlers.wordTags());
-        Assert.assertEquals("[WordTagsDto{word='五星红旗', tags=[]}, WordTagsDto{word='毛主席', tags=[]}, WordTagsDto{word='天安门', tags=[]}]", wordList1.toString());
+        Assert.assertEquals("[WordTagsDto{word='五星红旗', tags=null}, WordTagsDto{word='毛主席', tags=[0]}, WordTagsDto{word='天安门', tags=null}]", wordList1.toString());
+
+        Map<String, Set<String>> wordMap = new HashMap<>();
+        wordMap.put("五星红旗", new HashSet<>(Arrays.asList("政治", "国家")));
+        wordMap.put("毛主席", new HashSet<>(Arrays.asList("政治", "伟人", "国家")));
+        wordMap.put("天安门", new HashSet<>(Arrays.asList("政治", "国家", "地址")));
 
         List<WordTagsDto> wordList2 = SensitiveWordBs.newInstance()
-                .wordTag(WordTags.file("D:\\github\\sensitive-word\\src\\test\\resources\\dict_tag_test.txt"))
+                .wordTag(WordTags.map(wordMap))
                 .init()
                 .findAll(text, WordResultHandlers.wordTags());
         Assert.assertEquals("[WordTagsDto{word='五星红旗', tags=[政治, 国家]}, WordTagsDto{word='毛主席', tags=[政治, 伟人, 国家]}, WordTagsDto{word='天安门', tags=[政治, 国家, 地址]}]", wordList2.toString());