Extract tf-idf vectors with lucene

Question

I have indexed a set of documents using lucene. I also have stored DocumentTermVector for each document content. I wrote a program and got the term frequency vector for each document, but how can I get tf-idf vector of each document?

Here is my code that outputs term frequencies in each document:

Directory dir = FSDirectory.open(new File(indexDir));
    IndexReader ir = IndexReader.open(dir);
    for (int docNum=0; docNum<ir.numDocs(); docNum++) {
        System.out.println(ir.document(docNum).getField("filename").stringValue());
        TermFreqVector tfv = ir.getTermFreqVector(docNum, "contents");
        if (tfv == null) {
        // ignore empty fields
        continue;
        }
        String terms[] = tfv.getTerms();
        int termCount = terms.length;
        int freqs[] = tfv.getTermFrequencies();

        for (int t=0; t < termCount; t++) {
        System.out.println(terms[t] + " " + freqs[t]);
        }
    }

Is there any buit-in function in lucene for me to do that?

---

Nobody helped, and I did it by myself:

    Directory dir = FSDirectory.open(new File(indexDir));
    IndexReader ir = IndexReader.open(dir);

    int docNum;
    for (docNum = 0; docNum<ir.numDocs(); docNum++) {
        TermFreqVector tfv = ir.getTermFreqVector(docNum, "title");
        if (tfv == null) {
                // ignore empty fields
                continue;
        }
        String tterms[] = tfv.getTerms();
        int termCount = tterms.length;
        int freqs[] = tfv.getTermFrequencies();

        for (int t=0; t < termCount; t++) {
            double idf = ir.numDocs()/ir.docFreq(new Term("title", tterms[t]));
            System.out.println(tterms[t] + " " + freqs[t]*Math.log(idf));
        }
    }

is there any way to find the ID number of each term?

---

Nobody helped, and I did it by myself again:

    List list = new LinkedList();
    terms = null;
    try
    {
        terms = ir.terms(new Term("title", ""));
        while ("title".equals(terms.term().field()))
        {
        list.add(terms.term().text());
        if (!terms.next())
            break;
        }
    }
    finally
    {
        terms.close();
    }
    int docNum;
    for (docNum = 0; docNum<ir.numDocs(); docNum++) {
        TermFreqVector tfv = ir.getTermFreqVector(docNum, "title");
        if (tfv == null) {
                // ignore empty fields
                continue;
        }
        String tterms[] = tfv.getTerms();
        int termCount = tterms.length;
        int freqs[] = tfv.getTermFrequencies();

        for (int t=0; t < termCount; t++) {
            double idf = ir.numDocs()/ir.docFreq(new Term("title", tterms[t]));
            System.out.println(Collections.binarySearch(list, tterms[t]) + " " + tterms[t] + " " + freqs[t]*Math.log(idf));
        }
    }

Answer 1

You'll probably not found a tf-idf vector. But as you've already done, you can calculate IDF by hand. It is probably better to use the DefaultSimilarity (or whatever Similarity implementation you are using) to calculate it for you.

Regarding Term ID, I think currently you can't. At least not until Lucene 4.0, see this.