From e19bfa2ff762b9b497ac2e5d72962f6ea2524d2b Mon Sep 17 00:00:00 2001
From: p7mpv4cbt <1352787923@qq.com>
Date: Wed, 5 Nov 2025 11:28:22 +0800
Subject: [PATCH] ADD file via upload

---
 WordAnalyzer.java | 60 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 60 insertions(+)
 create mode 100644 WordAnalyzer.java

diff --git a/WordAnalyzer.java b/WordAnalyzer.java
new file mode 100644
index 0000000..fdb599b
--- /dev/null
+++ b/WordAnalyzer.java
@@ -0,0 +1,60 @@
+// src/main/java/com/llm/analysis/WordAnalyzer.java
+package com.llm.analysis;
+
+import com.hankcs.hanlp.HanLP;
+import com.hankcs.hanlp.dictionary.stopword.CoreStopWordDictionary;
+import com.hankcs.hanlp.seg.common.Term;
+import java.util.*;
+import java.util.stream.Collectors;
+
+public class WordAnalyzer {
+
+    // 目标关键词 (用于筛选相关弹幕，已转小写)
+    private static final List<String> LLM_KEYWORDS = Arrays.asList(
+            "大语言模型", "大模型", "llm", "gpt", "ai", "人工智能", "chatgpt", "文心一言", "通义千问", "讯飞星火"
+    );
+
+    /**
+     * 对弹幕列表进行分词、筛选和词频统计，并返回Top N结果。
+     * @param danmuList 原始弹幕列表
+     * @param topN 需要返回的Top数量
+     * @return 包含词语和频次的Map列表
+     */
+    public static List<Map.Entry<String, Long>> analyzeAndGetTopN(List<String> danmuList, int topN) {
+        // 1. 筛选包含LLM关键词的弹幕
+        List<String> relevantDanmus = danmuList.stream()
+                // 检查弹幕 d (已转小写) 是否包含任何一个关键词 (也转小写)
+                .filter(d -> LLM_KEYWORDS.stream().anyMatch(keyword -> d.contains(keyword.toLowerCase())))
+                .collect(Collectors.toList());
+
+        System.out.println("筛选出包含LLM关键词的弹幕：" + relevantDanmus.size() + " 条。");
+
+        // 2. 中文分词和计数
+        Map<String, Long> wordCounts = new HashMap<>();
+        for (String danmu : relevantDanmus) {
+            // HanLP分词
+            List<Term> termList = HanLP.segment(danmu);
+            
+            for (Term term : termList) {
+                String word = term.word.trim();
+                
+                // 进一步过滤：
+                // 1. 词语长度大于 1
+                // 2. 核心停用词过滤 (FIXED: 传入 word，而非 term)
+                // 3. 过滤掉纯数字或特殊符号
+                if (word.length() > 1 
+                        && !CoreStopWordDictionary.contains(word) // <-- 修正：传入 String 类型的 word
+                        && word.matches(".*[\\u4e00-\\u9fa5a-zA-Z0-9]+.*")) { 
+                    
+                    wordCounts.put(word, wordCounts.getOrDefault(word, 0L) + 1);
+                }
+            }
+        }
+        
+        // 3. 排序并获取 Top N
+        return wordCounts.entrySet().stream()
+                .sorted(Map.Entry.<String, Long>comparingByValue().reversed())
+                .limit(topN)
+                .collect(Collectors.toList());
+    }
+}
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