Question

我目前正在尝试计算lucene索引中术语的tf-idf矩阵。我尝试使用以下函数执行此操作：

public Table<Integer, BytesRef, Double> tfidf(String field) throws IOException, ParseException{
    //variables in complete context
    int totalNoOfDocs = reader.numDocs();                                   //total no of docs
    HashBasedTable<Integer, BytesRef, Double> tfidfPerDocAndTerm = HashBasedTable.create(); //tfidf value for each document(integer) and term(Byteref) pair.

    //variables in loop context
    BytesRef    term;                                                       //term as BytesRef
    int         noOfDocs;                                                   //number of documents (a term occours in)
    int         tf;                                                         //term frequency (of a term in a doc)
    double      idf;                                                        //inverse document frequency (of a term in a doc)
    double      tfidf;                                                      //term frequency - inverse document frequency value (of a term in a doc)
    Terms       termVector;                                                 //all terms of current doc in current field
    TermsEnum   termsEnum;                                                  //iterator for terms
    DocsEnum    docsEnum;                                                   //iterator for documents (of current term)

    List<Integer> docIds = getDocIds(totalNoOfDocs);                        //get internal documentIds of documents

    try {
        for(int doc : docIds){
            termVector  = reader.getTermVector(doc, field);                 //get termvector for document
            termsEnum   = termVector.iterator(null);                        //get iterator of termvector to iterate over terms


            while((term = termsEnum.next()) != null){                       //iterate of terms

                    noOfDocs = termsEnum.docFreq();                         //add no of docs the term occurs in to list

                    docsEnum = termsEnum.docs(null, null);                  //get document iterator for this term (all documents the term occours in)
                    while((doc = docsEnum.nextDoc()) != DocIdSetIterator.NO_MORE_DOCS){ //iterate over documents - computation of all tf-idf values for this term
                        tf      = docsEnum.freq();                          //get termfrequency of current term in current doc
                        idf     = Math.log((double)totalNoOfDocs / (double)noOfDocs); //calculate idf
                        tfidf   = (double) tf * idf;                        //caculate tfidf
                        tfidfPerDocAndTerm.put(doc, term, tfidf);           //add tf-idf value to matrix

                    }
            }
        }

    } catch (IOException ex) {
        Logger.getLogger(Index.class.getName()).log(Level.SEVERE, null, ex);
    }   
    return tfidfPerDocAndTerm;
}

问题是：noOfDocs = termsEnum.docFreq（）;总是返回1.即使有明显的术语出现在多个文档中（通过打印“术语”手动检查）。

我还发现，docsEnum我检索的是：docsEnum = termsEnum.docs（null，null）;总是只包含1个文档（doc 0）。

创建索引时，我使用带有停用词列表的标准分析器，因此所有术语都是小写的。

那么我的问题是什么？：/

感谢您的帮助！

Answer 1

实际上，你的术语是BytesRef类型，是循环而不是你的termsenums，但不幸的是，BytesRef不支持一个名为freq（）或docfreq（）的方法

Answer 2

实际上，枚举器总是返回1.但是你可以使用CollectionStatistics得到正确的值：

DefaultSimilarity similarity = new DefaultSimilarity();

IndexReader reader = searcher.getIndexReader();
IndexReaderContext context = searcher.getTopReaderContext();
CollectionStatistics collectionStats = searcher.collectionStatistics(FIELD);
long totalDocCount = collectionStats.docCount();

Terms termVector = reader.getTermVector(docId, FIELD);
TermsEnum iterator = termVector.iterator(null);

while (true) {
    BytesRef ref = iterator.next();
    if (ref == null) {
        break;
    }

    long termFreq = iterator.totalTermFreq();
    float tf = similarity.tf(termFreq);

    Term term = new Term(FIELD, ref);
    TermContext termContext = TermContext.build(context, term);

    TermStatistics termStats = searcher.termStatistics(term, termContext);
    long docFreq = termStats.docFreq();
    float idf = similarity.idf(docFreq, totalDocCount);

    // do something with tf and idf
}

请注意，要使其工作，您需要在索引中存储术语向量。

Lucene - 获取文档频率 - termsEnum.docFreq（）始终返回1

2 个答案: