Examples with structures._Word structures._Word used on opensource projects

Example 51 with structures._Word

use of structures._Word in project IR_Base by Linda-sunshine.

the class ACCTM_test method printChildTopicAssignment.

protected void printChildTopicAssignment(_Doc d, File topicFolder) {
    // System.out.println("printing topic assignment parent documents");
    String topicAssignmentFile = d.getName() + ".txt";
    try {
        PrintWriter pw = new PrintWriter(new File(topicFolder, topicAssignmentFile));
        for (_Word w : d.getWords()) {
            int index = w.getIndex();
            int topic = w.getTopic();
            String featureName = m_corpus.getFeature(index);
            pw.print(featureName + ":" + topic + "\t");
        }
        pw.flush();
        pw.close();
    } catch (FileNotFoundException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }
}

Example 52 with structures._Word

use of structures._Word in project IR_Base by Linda-sunshine.

the class DCMCorrLDA method cal_logLikelihood_partial4Child.

protected double cal_logLikelihood_partial4Child(_ChildDoc cDoc) {
    double childLikelihood = 0;
    _ParentDoc4DCM pDoc = (_ParentDoc4DCM) cDoc.m_parentDoc;
    for (_Word w : cDoc.getTestWords()) {
        int wid = w.getIndex();
        double wordLogLikelihood = 0;
        for (int k = 0; k < number_of_topics; k++) {
            double wordPerTopicLikelihood = cDoc.m_topics[k] * pDoc.m_wordTopic_prob[k][wid];
            wordLogLikelihood += wordPerTopicLikelihood;
        }
        childLikelihood += Math.log(wordLogLikelihood);
    }
    return childLikelihood;
}

Example 53 with structures._Word

use of structures._Word in project IR_Base by Linda-sunshine.

the class DCMCorrLDA method initTest.

protected void initTest(ArrayList<_Doc> sampleTestSet, _Doc d) {
    _ParentDoc4DCM pDoc = (_ParentDoc4DCM) d;
    for (_Stn stnObj : pDoc.getSentences()) {
        stnObj.setTopicsVct(number_of_topics);
    }
    int testLength = 0;
    pDoc.setTopics4GibbsTest(number_of_topics, 0, testLength, vocabulary_size);
    sampleTestSet.add(pDoc);
    for (_ChildDoc cDoc : pDoc.m_childDocs) {
        testLength = (int) (m_testWord4PerplexityProportion * cDoc.getTotalDocLength());
        cDoc.setTopics4GibbsTest(number_of_topics, d_alpha, testLength);
        for (_Word w : cDoc.getWords()) {
            int wid = w.getIndex();
            int tid = w.getTopic();
            pDoc.m_wordTopic_stat[tid][wid]++;
            pDoc.m_topic_stat[tid]++;
        }
        sampleTestSet.add(cDoc);
        cDoc.createSparseVct4Infer();
        // cDoc computeMu
        computeTestMu4Doc(cDoc);
    }
}

Example 54 with structures._Word

use of structures._Word in project IR_Base by Linda-sunshine.

the class DCMCorrLDA_multi_E_test method rankChild4StnByLikelihood.

protected HashMap<String, Double> rankChild4StnByLikelihood(_Stn stnObj, _ParentDoc4DCM pDoc) {
    HashMap<String, Double> likelihoodMap = new HashMap<String, Double>();
    for (_ChildDoc cDoc : pDoc.m_childDocs) {
        double stnLogLikelihood = 0;
        for (_Word w : stnObj.getWords()) {
            double wordLikelihood = 0;
            int wid = w.getIndex();
            for (int k = 0; k < number_of_topics; k++) {
                wordLikelihood += cDoc.m_topics[k] * pDoc.m_wordTopic_prob[k][wid];
            }
            stnLogLikelihood += wordLikelihood;
        }
        likelihoodMap.put(cDoc.getName(), stnLogLikelihood);
    }
    return likelihoodMap;
}

Example 55 with structures._Word

use of structures._Word in project IR_Base by Linda-sunshine.

the class DCMCorrLDA_test method rankChild4StnByLikelihood.

protected HashMap<String, Double> rankChild4StnByLikelihood(_Stn stnObj, _ParentDoc4DCM pDoc) {
    HashMap<String, Double> likelihoodMap = new HashMap<String, Double>();
    for (_ChildDoc cDoc : pDoc.m_childDocs) {
        double stnLogLikelihood = 0;
        for (_Word w : stnObj.getWords()) {
            double wordLikelihood = 0;
            int wid = w.getIndex();
            for (int k = 0; k < number_of_topics; k++) {
                wordLikelihood += childTopicInDocProb(k, cDoc, pDoc) * childWordByTopicProb(k, wid, pDoc);
            }
            stnLogLikelihood += wordLikelihood;
        }
        likelihoodMap.put(cDoc.getName(), stnLogLikelihood);
    }
    return likelihoodMap;
}