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

Example 51 with structures._Stn

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

the class corrLDA_Gibbs method initTest4Dynamical.

public void initTest4Dynamical(ArrayList<_Doc> sampleTestSet, _Doc d, int commentNum) {
    _ParentDoc pDoc = (_ParentDoc) d;
    pDoc.m_childDocs4Dynamic = new ArrayList<_ChildDoc>();
    pDoc.setTopics4Gibbs(number_of_topics, 0);
    for (_Stn stnObj : pDoc.getSentences()) {
        stnObj.setTopicsVct(number_of_topics);
    }
    sampleTestSet.add(pDoc);
    int count = 0;
    for (_ChildDoc cDoc : pDoc.m_childDocs) {
        if (count >= commentNum) {
            break;
        }
        count++;
        cDoc.setTopics4Gibbs_LDA(number_of_topics, 0);
        sampleTestSet.add(cDoc);
        pDoc.addChildDoc4Dynamics(cDoc);
    }
}

Example 52 with structures._Stn

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

the class weightedCorrespondenceModel method initialize_probability.

@Override
protected void initialize_probability(Collection<_Doc> collection) {
    init();
    for (_Doc d : collection) {
        if (d instanceof _ParentDoc4DCM) {
            int totalWords = 0;
            double totalLambda = 0;
            m_parentDocNum += 1;
            _ParentDoc4DCM pDoc = (_ParentDoc4DCM) d;
            pDoc.setTopics4Variational(number_of_topics, d_alpha, vocabulary_size, d_beta);
            totalWords += pDoc.getTotalDocLength();
            for (_Stn stnObj : pDoc.getSentences()) stnObj.setTopicsVct(number_of_topics);
            for (_ChildDoc cDoc : pDoc.m_childDocs) {
                totalWords += cDoc.getTotalDocLength();
                m_childDocNum += 1;
                cDoc.setTopics4Variational(number_of_topics, d_alpha);
                // update the article thread sufficient statistics
                for (int n = 0; n < cDoc.getSparse().length; n++) {
                    _SparseFeature fv = cDoc.getSparse()[n];
                    int wID = fv.getIndex();
                    double wVal = fv.getValue();
                    for (int k = 0; k < number_of_topics; k++) {
                        pDoc.m_lambda_stat[k][wID] += cDoc.m_phi[n][k] * wVal;
                    }
                }
            }
            for (int k = 0; k < number_of_topics; k++) {
                pDoc.m_lambda_topicStat[k] = Utils.sumOfArray(pDoc.m_lambda_stat[k]);
                totalLambda += pDoc.m_lambda_topicStat[k];
            }
        // System.out.println("totalWords\t"+totalWords+"\t"+totalLambda);
        }
    }
    imposePrior();
}

Example 53 with structures._Stn

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

the class languageModelBaseLine method printTopChild4Stn.

protected void printTopChild4Stn(String filePrefix) {
    String topChild4StnFile = filePrefix + "/topChild4Stn.txt";
    try {
        PrintWriter pw = new PrintWriter(new File(topChild4StnFile));
        for (_Doc d : m_corpus.getCollection()) {
            if (d instanceof _ParentDoc) {
                _ParentDoc pDoc = (_ParentDoc) d;
                pw.println(pDoc.getName() + "\t" + pDoc.getSenetenceSize());
                for (_Stn stnObj : pDoc.getSentences()) {
                    // HashMap<String, Double> likelihoodMap = rankChild4StnByLikelihood(stnObj, pDoc);
                    HashMap<String, Double> likelihoodMap = rankChild4StnByLanguageModel(stnObj, pDoc);
                    // int i=0;
                    pw.print((stnObj.getIndex() + 1) + "\t");
                    for (Map.Entry<String, Double> e : sortHashMap4String(likelihoodMap, true)) {
                        // if(i==topK)
                        // break;
                        pw.print(e.getKey());
                        pw.print(":" + e.getValue());
                        pw.print("\t");
                    // i++;
                    }
                    pw.println();
                }
            }
        }
        pw.flush();
        pw.close();
    } catch (Exception e) {
        e.printStackTrace();
    }
}

Example 54 with structures._Stn

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

the class languageModelBaseLine method rankChild4StnByLikelihood.

protected HashMap<String, Double> rankChild4StnByLikelihood(_Stn stnObj, _ParentDoc pDoc) {
    HashMap<String, Double> childLikelihoodMap = new HashMap<String, Double>();
    for (_ChildDoc cDoc : pDoc.m_childDocs) {
        int cDocLen = cDoc.getTotalDocLength();
        _SparseFeature[] fv = cDoc.getSparse();
        double stnLogLikelihood = 0;
        double alphaDoc = m_smoothingMu / (m_smoothingMu + cDocLen);
        _SparseFeature[] sv = stnObj.getFv();
        for (_SparseFeature svWord : sv) {
            double featureLikelihood = 0;
            int wid = svWord.getIndex();
            double stnVal = svWord.getValue();
            int featureIndex = Utils.indexOf(fv, wid);
            if (featureIndex == -1)
                continue;
            double docVal = fv[featureIndex].getValue();
            double smoothingProb = docVal / (m_smoothingMu + cDocLen);
            smoothingProb += m_smoothingMu * m_wordSstat.get(wid) / (m_smoothingMu + cDocLen);
            featureLikelihood = Math.log(smoothingProb / (alphaDoc * m_wordSstat.get(wid)));
            stnLogLikelihood += stnVal * featureLikelihood;
        }
        stnLogLikelihood += stnObj.getLength() * Math.log(alphaDoc);
        childLikelihoodMap.put(cDoc.getName(), stnLogLikelihood);
    }
    return childLikelihoodMap;
}

Example 55 with structures._Stn

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

the class HTMM method ComputeEmissionProbsForDoc.

// Construct the emission probabilities for sentences under different topics in a particular document.
void ComputeEmissionProbsForDoc(_Doc d) {
    for (int i = 0; i < d.getSenetenceSize(); i++) {
        _Stn stn = d.getSentence(i);
        Arrays.fill(emission[i], 0);
        for (int k = 0; k < this.number_of_topics; k++) {
            for (_SparseFeature w : stn.getFv()) {
                // all in log-space
                emission[i][k] += w.getValue() * topic_term_probabilty[k][w.getIndex()];
            }
        }
    }
}