lucene3.4文档得分

public static void main(String[] args) throws Exception { 
    Directory dir =new RAMDirectory();
   
    IndexWriterConfig conf = new IndexWriterConfig(Version.LUCENE_34, new StandardAnalyzer(Version.LUCENE_34));
    IndexWriter writer = new IndexWriter(dir,conf); 

         
        Document doc1 = new Document(); 
        Document doc2 = new Document(); 
        Document doc3 = new Document();
        Document doc4 = new Document(); 
        Document doc5 = new Document(); 
         
        Field f1 = new Field("sex","1", Field.Store.YES, Field.Index.ANALYZED); 
        Field f2 = new Field("sex","0", Field.Store.YES, Field.Index.ANALYZED); 
        Field f3 = new Field("sex","1", Field.Store.YES, Field.Index.ANALYZED);
        Field f4 = new Field("sex","1", Field.Store.YES, Field.Index.ANALYZED);
        Field f5 = new Field("sex","1", Field.Store.YES, Field.Index.ANALYZED);
       
        Field f11 = new Field("income","10", Field.Store.YES, Field.Index.ANALYZED); 
        Field f22 = new Field("income","10", Field.Store.YES, Field.Index.ANALYZED); 
        Field f33 = new Field("income","11", Field.Store.YES, Field.Index.ANALYZED);
        Field f44 = new Field("income","10", Field.Store.YES, Field.Index.ANALYZED);
        Field f55 = new Field("income","10", Field.Store.YES, Field.Index.ANALYZED);
         
        doc1.add(f1); 
        doc2.add(f2); 
        doc3.add(f3);
        doc4.add(f4);
        doc5.add(f5);
       
        doc1.add(f11); 
        doc2.add(f22); 
        doc3.add(f33);
        doc4.add(f44);
        doc5.add(f55);
        doc5.setBoost(2f);
         
        writer.addDocument(doc1); 
        writer.addDocument(doc2); 
        writer.addDocument(doc3);
        writer.addDocument(doc4); 
        writer.addDocument(doc5);
         
        writer.close(); 
         
        IndexSearcher searcher = new IndexSearcher(dir); 
        //TermQuery q = new TermQuery(new Term("sex", "1")); 
        //q.setBoost(2f);
        QueryParser qp=new QueryParser(Version.LUCENE_34, "nickname",new StandardAnalyzer(Version.LUCENE_34));
        Query q=qp.parse("sex:1 AND income:10");
        TopDocs hits = searcher.search(q,100);

       
        for(int i=0;i<hits.scoreDocs.length;i++){
ScoreDoc sdoc = hits.scoreDocs[i]; 
Document doc = searcher.doc(sdoc.doc);
System.out.print(doc.get("sex") + "\t\t"); 
         System.out.println(sdoc.score); 
         System.out.println(searcher.explain(q, sdoc.doc));//
}
       
        /*for(int docID=0; docID<hits.length;docID++){ 
            Document doc = searcher.doc(hits[docID].doc); 
            System.out.print(doc.get("sex") + "\t\t"); 
            System.out.println(hits[docID].score); 
            System.out.println(searcher.explain(q, docID));// 
        }  */
    } 

输出结果
1 2.828427
2.828427 = (MATCH) sum of:
  1.4142135 = (MATCH) weight(sex:1 in 4), product of:
    0.70710677 = queryWeight(sex:1), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    2.0 = (MATCH) fieldWeight(sex:1 in 4), product of:
      1.0 = tf(termFreq(sex:1)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      2.0 = fieldNorm(field=sex, doc=4)
  1.4142135 = (MATCH) weight(income:10 in 4), product of:
    0.70710677 = queryWeight(income:10), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    2.0 = (MATCH) fieldWeight(income:10 in 4), product of:
      1.0 = tf(termFreq(income:10)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      2.0 = fieldNorm(field=income, doc=4)

1 1.4142135
1.4142135 = (MATCH) sum of:
  0.70710677 = (MATCH) weight(sex:1 in 0), product of:
    0.70710677 = queryWeight(sex:1), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    1.0 = (MATCH) fieldWeight(sex:1 in 0), product of:
      1.0 = tf(termFreq(sex:1)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      1.0 = fieldNorm(field=sex, doc=0)
  0.70710677 = (MATCH) weight(income:10 in 0), product of:
    0.70710677 = queryWeight(income:10), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    1.0 = (MATCH) fieldWeight(income:10 in 0), product of:
      1.0 = tf(termFreq(income:10)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      1.0 = fieldNorm(field=income, doc=0)

1 1.4142135
1.4142135 = (MATCH) sum of:
  0.70710677 = (MATCH) weight(sex:1 in 3), product of:
    0.70710677 = queryWeight(sex:1), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    1.0 = (MATCH) fieldWeight(sex:1 in 3), product of:
      1.0 = tf(termFreq(sex:1)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      1.0 = fieldNorm(field=sex, doc=3)
  0.70710677 = (MATCH) weight(income:10 in 3), product of:
    0.70710677 = queryWeight(income:10), product of:
      1.0 = idf(docFreq=4, maxDocs=5)
      0.70710677 = queryNorm
    1.0 = (MATCH) fieldWeight(income:10 in 3), product of:
      1.0 = tf(termFreq(income:10)=1)
      1.0 = idf(docFreq=4, maxDocs=5)
      1.0 = fieldNorm(field=income, doc=3)

score简单说是由各个字段的 tf * idf * boost * lengthNorm相加计算得出的。每个字段又分为 queryWeight，fieldWeight