java实现ES搜索算法计算相似度匹配 全代码示例

在Java中，我们通常会使用Elasticsearch (ES) 的 Java 客户端API来执行搜索并计算文档之间的相似度。Elasticsearch本身并不直接提供相似度搜索功能，但我们可以通过`Match`查询、`Similarity`分析器以及第三方库如`Apache Tika`或`Jaccard Similarity`等来实现。

这里是一个简单的示例，使用Tika的Jaccard Similarity来计算两个文本的相似度：

import org.apache.tika.languagedetect.LanguageDetector;
import org.apache.tika.metadata.Metadata;
import org.apache.tika.parser.ParseContext;
import org.apache.tika.parser.Parser;
import org.apache.tika.sax.BodyContentHandler;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.HumanReadableQuery;
import org.elasticsearch.search.builder.SearchSourceBuilder;

public class ElasticsearchSimilarityExample {
    private static final RestHighLevelClient CLIENT = ... // 获取ES客户端实例

    public static double calculateSimilarity(String docId1, String docId2) throws Exception {
        // 假设我们已经安装了tika-server作为服务
        LanguageDetector langDetector = new LanguageDetector();
        Parser parser = new Parser(new ParseContext() {
            @Override
            public LanguageDetector getLanguageDetector() {
                return langDetector;
            }
        });

        BodyContentHandler handler1 = new BodyContentHandler();
        parser.parse(CLIENT.prepareGet(docId1).get(), handler1);
        String content1 = handler1.toString();

        BodyContentHandler handler2 = new BodyContentHandler();
        parser.parse(CLIENT.prepareGet(docId2).get(), handler2);
        String content2 = handler2.toString();

        // 使用Jaccard Similarity
        double[] termFrequencies1 = extractTermFrequencies(content1);
        double[] termFrequencies2 = extractTermFrequencies(content2);

        // 计算Jaccard相似度
        double similarity = JaccardCoefficient.calculate(termFrequencies1, termFrequencies2);
        return similarity;
    }

    private static double[] extractTermFrequencies(String text) {
        // 这里只是一个简化版本，实际操作需要更复杂的解析和频率统计
        // 可能需要用到停用词列表和分词工具
        List<String> terms = ...; // 分词后的术语列表
        return terms.stream().mapToDouble(Double::valueOf).toArray();
    }

    // 更详细的搜索请求，包括设置相似度查询
    public static SearchResponse searchWithSimilarity(String query, String docType) {
        HumanReadableQuery humanQuery = new HumanReadableQuery(query, "match");
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder()
                .query(humanQuery)
                .addSort("similarity_score", SortOrder.DESC); // 排序按相似度降序
        SearchRequest request = new SearchRequest(docType);
        request.source(sourceBuilder);
        
        // 发起搜索请求并获取结果
        SearchResponse response = CLIENT.search(request, RequestOptions.DEFAULT);
        return response;
    }