Generate Term-Document matrix using Lucene 4.4

I'm trying to create Term-Document matrix for a small corpus to further experiment with LSI. However, I couldn't find a way to do it with Lucene 4.4.

I know how to get TermVector for each document as following:

//create boolean query to search for a specific document (not shown)
TopDocs hits = searcher.search(query, 1);    
Terms termVector = reader.getTermVector(hits.scoreDocs[0].doc, "contents");
System.out.println(termVector.size());  //just testing

I thought I can just union all the termVector together as columns in a matrix to get the matrix. However, termVector for different documents have different size. And we don't know how to pad 0 into the termVector. So, certainly, this method does not work.

1. Hence, I wonder if someone can show me how to create Term-Document vector with Lucene 4.4 please? (If possible, please show sample code).

2. If Lucene does not support this function, what is the other way you recommend to do it?

   Many thanks,

I found the solution to my problem here. Very detail example given by Mr. Sujit, although the code is written in older version of Lucene so many things will have to be changed. I'll update details when I finish my code. Here is my solution that works on Lucene 4.4

public class BuildTermDocumentMatrix {
public BuildTermDocumentMatrix(File index, File corpus) throws IOException{
    reader = DirectoryReader.open(FSDirectory.open(index));
    searcher = new IndexSearcher(reader);
    this.corpus = corpus;
    termIdMap = computeTermIdMap(reader);
}   
/**
*  Map term to a fix integer so that we can build document matrix later.
*  It's used to assign term to specific row in Term-Document matrix
*/
private Map<String, Integer> computeTermIdMap(IndexReader reader) throws IOException {
    Map<String,Integer> termIdMap = new HashMap<String,Integer>();
    int id = 0;
    Fields fields = MultiFields.getFields(reader);
    Terms terms = fields.terms("contents");
    TermsEnum itr = terms.iterator(null);
    BytesRef term = null;
    while ((term = itr.next()) != null) {               
        String termText = term.utf8ToString();              
        if (termIdMap.containsKey(termText))
            continue;
        //System.out.println(termText); 
        termIdMap.put(termText, id++);
    }

    return termIdMap;
}

/**
*  build term-document matrix for the given directory
*/
public RealMatrix buildTermDocumentMatrix () throws IOException {
    //iterate through directory to work with each doc
    int col = 0;
    int numDocs = countDocs(corpus);            //get the number of documents here      
    int numTerms = termIdMap.size();    //total number of terms     
    RealMatrix tdMatrix = new Array2DRowRealMatrix(numTerms, numDocs);

    for (File f : corpus.listFiles()) {
        if (!f.isHidden() && f.canRead()) {
            //I build term document matrix for a subset of corpus so
            //I need to lookup document by path name. 
            //If you build for the whole corpus, just iterate through all documents
            String path = f.getPath();
            BooleanQuery pathQuery = new BooleanQuery();
            pathQuery.add(new TermQuery(new Term("path", path)), BooleanClause.Occur.SHOULD);
            TopDocs hits = searcher.search(pathQuery, 1);

            //get term vector
            Terms termVector = reader.getTermVector(hits.scoreDocs[0].doc, "contents");
            TermsEnum itr = termVector.iterator(null);
            BytesRef term = null;

            //compute term weight
            while ((term = itr.next()) != null) {               
                String termText = term.utf8ToString();              
                int row = termIdMap.get(termText);
                long termFreq = itr.totalTermFreq();
                long docCount = itr.docFreq();
                double weight = computeTfIdfWeight(termFreq, docCount, numDocs);
                tdMatrix.setEntry(row, col, weight);
            }
            col++;
        }
    }       
    return tdMatrix;
}
}