Lucene的评分(score)机制研究

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首先，需要学习Lucene的评分计算公式——

分值计算方式为查询语句q中每个项t与文档d的匹配分值之和，当然还有权重的因素。其中每一项的意思如下表所示：

通过Searcher.explain(Query query, int doc)方法可以查看某个文档的得分的具体构成。 示例：

public class ScoreSortTest {
    public final static String INDEX_STORE_PATH = "index";
    public static void main(String[] args) throws Exception {
        IndexWriter writer = new IndexWriter(INDEX_STORE_PATH, new StandardAnalyzer(), true);
        writer.setUseCompoundFile(false);
        
        Document doc1 = new Document();
        Document doc2 = new Document();
        Document doc3 = new Document();
        
        Field f1 = new Field("bookname","bc bc", Field.Store.YES, Field.Index.TOKENIZED);
        Field f2 = new Field("bookname","ab bc", Field.Store.YES, Field.Index.TOKENIZED);
        Field f3 = new Field("bookname","ab bc cd", Field.Store.YES, Field.Index.TOKENIZED);
        
        doc1.add(f1);
        doc2.add(f2);
        doc3.add(f3);
        
        writer.addDocument(doc1);
        writer.addDocument(doc2);
        writer.addDocument(doc3);
        
        writer.close();
        
        IndexSearcher searcher = new IndexSearcher(INDEX_STORE_PATH);
        TermQuery q = new TermQuery(new Term("bookname", "bc"));
        q.setBoost(2f);
        Hits hits = searcher.search(q);
        for(int i=0; i<hits.length();i++){
            Document doc = hits.doc(i);
            System.out.print(doc.get("bookname") + "\t\t");
            System.out.println(hits.score(i));
            System.out.println(searcher.explain(q, hits.id(i)));//
        }
    }
}

运行结果： 

bc bc    0.629606 
0.629606 = (MATCH) fieldWeight(bookname:bc in 0), product of: 
  1.4142135 = tf(termFreq(bookname:bc)=2) 
  0.71231794 = idf(docFreq=3, numDocs=3) 
  0.625 = fieldNorm(field=bookname, doc=0) 

ab bc    0.4451987 
0.4451987 = (MATCH) fieldWeight(bookname:bc in 1), product of: 
  1.0 = tf(termFreq(bookname:bc)=1) 
  0.71231794 = idf(docFreq=3, numDocs=3) 
  0.625 = fieldNorm(field=bookname, doc=1) 

ab bc cd    0.35615897 
0.35615897 = (MATCH) fieldWeight(bookname:bc in 2), product of: 
  1.0 = tf(termFreq(bookname:bc)=1) 
  0.71231794 = idf(docFreq=3, numDocs=3) 
  0.5 = fieldNorm(field=bookname, doc=2) 

fieldWeight的计算

在org/apache/lucene/search/similarities/TFIDFSimilarity.java的explainScore方法中有：

1. // explain field weight
2.     Explanation fieldExpl = new Explanation();
3.     fieldExpl.setDescription("fieldWeight in "+doc+
4.                              ", product of:");
5.  
6.     Explanation tfExplanation = new Explanation();
7.     tfExplanation.setValue(tf(freq.getValue()));
8.     tfExplanation.setDescription("tf(freq="+freq.getValue()+"), with freq of:");
9.     tfExplanation.addDetail(freq);
10.     fieldExpl.addDetail(tfExplanation);
11.     fieldExpl.addDetail(stats.idf);
12.  
13.     Explanation fieldNormExpl = new Explanation();
14.     float fieldNorm = norms != null ? decodeNormValue(norms.get(doc)) : 1.0f;
15.     fieldNormExpl.setValue(fieldNorm);
16.     fieldNormExpl.setDescription("fieldNorm(doc="+doc+")");
17.     fieldExpl.addDetail(fieldNormExpl);
18.     
19.     fieldExpl.setValue(tfExplanation.getValue() *
20.                        stats.idf.getValue() *
21.                        fieldNormExpl.getValue());
22.  
23.     result.addDetail(fieldExpl);

重点是这一句：

1. fieldExpl.setValue(tfExplanation.getValue() *
2.                        stats.idf.getValue() *
3.                        fieldNormExpl.getValue());

使用计算式表示就是

fieldWeight = tf * idf * fieldNorm

tf和idf的计算参考前面的，fieldNorm的计算在索引的时候确定了，此时直接从索引文件中读取，这个方法并没有给出直接的计算。如果使用DefaultSimilarity的话，它实际上就是lengthNorm，域越长的话Norm越小，在org/apache/lucene/search/similarities/DefaultSimilarity.java里面有关于它的计算：

1.   public float lengthNorm(FieldInvertState state) {
2.     final int numTerms;
3.     if (discountOverlaps)
4.       numTerms = state.getLength() - state.getNumOverlap();
5.     else
6.       numTerms = state.getLength();
7.    return state.getBoost() * ((float) (1.0 / Math.sqrt(numTerms)));
8.   }

参考文献：

【1】http://www.hankcs.com/program/java/lucene-scoring-algorithm-explained.html

【2】http://grantbb.iteye.com/blog/181802

Lucene的评分(score)机制研究

标签：这一   lsp   文件中   实现   分享   包含   out   权重   技术分享   

原文地址：http://www.cnblogs.com/davidwang456/p/6150388.html