如何在Lucene中实现tf-idf和余弦相似度？

Question

如何在Lucene中实现tf-idf和余弦相似性？我正在使用Lucene 4.2。我创建的程序不使用tf-idf和Cosine similaryty，它只使用TopScoreDocCollector。

import com.mysql.jdbc.Statement; 
import java.io.BufferedReader; 
import java.io.File; 
import java.io.InputStreamReader; 
import org.apache.lucene.analysis.standard.StandardAnalyzer; 
import org.apache.lucene.util.Version; 
import org.apache.lucene.index.IndexWriterConfig; 
import org.apache.lucene.index.IndexWriter; 

import java.sql.DriverManager; 
import java.sql.Connection; 
import java.sql.ResultSet; 
import org.apache.lucene.analysis.id.IndonesianAnalyzer; 
import org.apache.lucene.document.Document; 
import org.apache.lucene.document.Field; 
import org.apache.lucene.index.*; 
import org.apache.lucene.queryparser.classic.ParseException; 
import org.apache.lucene.queryparser.classic.QueryParser; 
import org.apache.lucene.search.IndexSearcher; 
import org.apache.lucene.search.Query; 
import org.apache.lucene.search.ScoreDoc; 
import org.apache.lucene.search.TopScoreDocCollector; 
import org.apache.lucene.store.Directory; 
import org.apache.lucene.store.FSDirectory; 
import org.apache.lucene.store.RAMDirectory; 

public class IndexMysqlDBStemming { 

    public static void main(String[] args) throws Exception { 

    // 1. Create Index From Database 
    Class.forName("com.mysql.jdbc.Driver").newInstance(); 
    Connection connection = DriverManager.getConnection("jdbc:mysql://localhost/db_haiquran", "root", ""); 

    IndonesianAnalyzer analyzer = new IndonesianAnalyzer(Version.LUCENE_42); 
    //StandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_42); 
    QueryParser parser = new QueryParser(Version.LUCENE_42, "result", analyzer); 

    Directory INDEX_DIR = new RAMDirectory(); 

    IndexWriterConfig config = new IndexWriterConfig(Version.LUCENE_42, analyzer); 
    IndexWriter writer = new IndexWriter(INDEX_DIR, config); 

    String query = "SELECT * FROM ayat"; 
    java.sql.Statement statement = connection.createStatement(); 
    ResultSet result = statement.executeQuery(query); 

    while (result.next()) { 
     Document document = new Document(); 
     document.add(new Field("NO_INDEX_AYAT", result.getString("NO_INDEX_AYAT"), Field.Store.YES, Field.Index.NOT_ANALYZED)); 
     document.add(new Field("NO_SURAT", result.getString("NO_SURAT"), Field.Store.YES, Field.Index.NOT_ANALYZED)); 
     document.add(new Field("NO_AYAT", result.getString("NO_AYAT"), Field.Store.YES, Field.Index.NOT_ANALYZED)); 
     document.add(new Field("TEXT_INDO", result.getString("TEXT_INDO"), Field.Store.YES, Field.Index.ANALYZED)); 
     document.add(new Field("TEXT_ARAB", result.getString("TEXT_ARAB"), Field.Store.YES, Field.Index.NOT_ANALYZED)); 
     writer.updateDocument(new Term("NO_INDEX_AYAT", result.getString("NO_INDEX_AYAT")), document); 

    } 

    writer.close(); 


    // 2. Query 
    System.out.println("Enter your search keyword in here : "); 
    BufferedReader bufferRead = new BufferedReader(new InputStreamReader(System.in)); 
    String s = bufferRead.readLine(); 
    String querystr = args.length > 0 ? args[0] :s; 

    try { 
     System.out.println(parser.parse(querystr)+"\n"); //amenit 
     System.out.println(); 

    } catch (ParseException ex) { 
     // Exception 
    } 

    Query q = new QueryParser(Version.LUCENE_42, "TEXT_INDO", analyzer).parse(querystr); 

    // 3. Search 

    int hitsPerPage = 10; 
    IndexReader reader = DirectoryReader.open(INDEX_DIR); 
    IndexSearcher searcher = new IndexSearcher(reader); 
    TopScoreDocCollector collector = TopScoreDocCollector.create(hitsPerPage, true); 
    searcher.search(q, collector); 
    ScoreDoc[] hits = collector.topDocs().scoreDocs; 

    // 4. Display results 

    System.out.println("Found : " + hits.length + " hits."); 

    System.out.println("No" + " ID " + "\t" + " Surat " + "\t" + " No Ayat " + "\t" + " Terjemahan Ayat " + "\t" + " Teks Arab "); 

    for (int i=0; i<hits.length; i++) { 
     int docID = hits[i].doc; 
     Document d = searcher.doc(docID); 

     System.out.println((i+1) + ". " + d.get("NO_INDEX_AYAT") + "\t" + d.get("NO_SURAT") + "\t" + d.get("NO_AYAT")+ 
       "\t" + d.get("TEXT_INDO") + "\t" + d.get("TEXT_ARAB")); 

    } 

    reader.close();   
    } 
} 

如何使用tf-idf和余弦相似度显示计算结果？

Answer 1

除非有东西丢失，你已经完成了。做得好！

默认情况下使用的相似度算法是DefaultSimilarity，但您可以在其基类TFIDFSimilarity中找到大多数文档（和逻辑）。

TFIDFSimilarity确实是一个TF-IDF和余弦相似性评分模型的实现。