java实现中文字符串余弦相似度匹配

以下是Java实现中文字符串余弦相似度匹配的示例代码：

import java.util.HashMap;
import java.util.Map;

public class ChineseCosineSimilarity {

    public static double cosineSimilarity(String text1, String text2) {
        Map<String, Integer> wordFrequencyMap1 = new HashMap<>();
        Map<String, Integer> wordFrequencyMap2 = new HashMap<>();

        String[] words1 = text1.split("");
        String[] words2 = text2.split("");

        for (String word : words1) {
            if (wordFrequencyMap1.containsKey(word)) {
                wordFrequencyMap1.put(word, wordFrequencyMap1.get(word) + 1);
            } else {
                wordFrequencyMap1.put(word, 1);
            }
        }

        for (String word : words2) {
            if (wordFrequencyMap2.containsKey(word)) {
                wordFrequencyMap2.put(word, wordFrequencyMap2.get(word) + 1);
            } else {
                wordFrequencyMap2.put(word, 1);
            }
        }

        double dotProduct = 0.0;
        double normA = 0.0;
        double normB = 0.0;

        for (String word : wordFrequencyMap1.keySet()) {
            if (wordFrequencyMap2.containsKey(word)) {
                dotProduct += wordFrequencyMap1.get(word) * wordFrequencyMap2.get(word);
            }
            normA += Math.pow(wordFrequencyMap1.get(word), 2);
        }

        for (String word : wordFrequencyMap2.keySet()) {
            normB += Math.pow(wordFrequencyMap2.get(word), 2);
        }

        return dotProduct / (Math.sqrt(normA) * Math.sqrt(normB));
    }

    public static void main(String[] args) {
        String text1 = "你好，世界";
        String text2 = "世界，你好";
        double cosineSimilarity = cosineSimilarity(text1, text2);
        System.out.println("Cosine similarity: " + cosineSimilarity);
    }

}

在`cosineSimilarity`方法中，我们将每个字符串转换为单个字符，然后计算它们的词频。然后，我们可以计算两个字符串的余弦相似度。在`main`方法中，我们定义了两个中文字符串并计算它们的余弦相似度。需要注意的是，在中文字符串中，一个中文字符可能不是一个单词，因此我们将每个中文字符看作一个单词进行处理。