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

Example 61 with structures._RankItem

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

the class WeightedAvgTransAdapt method setPersonalizedModel.

@Override
public void setPersonalizedModel() {
    _CoLinAdaptStruct ui, uj;
    int k;
    for (int i = 0; i < m_userList.size(); i++) {
        ui = (_CoLinAdaptStruct) m_userList.get(i);
        for (int n = 0; n < m_featureSize + 1; n++) {
            k = m_featureGroupMap[n];
            m_pWeights[n] = ui.getSelfSim() * (m_gWeights[n] * ui.getScaling(k) + ui.getShifting(k));
        }
        // traverse all the neighbors
        for (_RankItem nit : ui.getNeighbors()) {
            uj = (_CoLinAdaptStruct) m_userList.get(nit.m_index);
            for (int n = 0; n < m_featureSize + 1; n++) {
                k = m_featureGroupMap[n];
                m_pWeights[n] += nit.m_value * (m_gWeights[n] * uj.getScaling(k) + uj.getShifting(k));
            }
        }
        ui.setPersonalizedModel(m_pWeights);
    }
}

Example 62 with structures._RankItem

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

the class WeightedAvgTransAdapt method logit.

@Override
protected // In this logit function, we need to sum over all the neighbors of the current user.
double logit(_SparseFeature[] fvs, _AdaptStruct user) {
    _CoLinAdaptStruct ui = (_CoLinAdaptStruct) user;
    double sum = ui.getSelfSim() * linearFunc(fvs, ui);
    // Traverse all neighbors of the current user.
    for (_RankItem nit : ui.getNeighbors()) {
        _CoLinAdaptStruct uj = (_CoLinAdaptStruct) m_userList.get(nit.m_index);
        sum += nit.m_value * linearFunc(fvs, uj);
    }
    return Utils.logistic(sum);
}

Example 63 with structures._RankItem

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

the class CLRWithDP method printInfo.

public void printInfo() {
    MyPriorityQueue<_RankItem> clusterRanker = new MyPriorityQueue<_RankItem>(5);
    // clear the statistics
    for (int i = 0; i < m_kBar; i++) {
        m_thetaStars[i].resetCount();
        clusterRanker.add(new _RankItem(i, m_thetaStars[i].getMemSize()));
    }
    // collect statistics across users in adaptation data
    _thetaStar theta = null;
    for (int i = 0; i < m_userList.size(); i++) {
        _DPAdaptStruct user = (_DPAdaptStruct) m_userList.get(i);
        theta = user.getThetaStar();
        for (_Review review : user.getReviews()) {
            if (review.getType() != rType.ADAPTATION)
                // only touch the adaptation data
                continue;
            else if (review.getYLabel() == 1)
                theta.incPosCount();
            else
                theta.incNegCount();
        }
    }
    System.out.print("[Info]Clusters:");
    for (int i = 0; i < m_kBar; i++) System.out.format("%s\t", m_thetaStars[i].showStat());
    System.out.print(String.format("\n[Info]%d Clusters are found in total!\n", m_kBar));
}

Example 64 with structures._RankItem

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

the class CLRWithHDP method printInfo.

public void printInfo(boolean printDetails) {
    MyPriorityQueue<_RankItem> clusterRanker = new MyPriorityQueue<_RankItem>(10);
    // clear the statistics
    for (int i = 0; i < m_kBar; i++) {
        m_hdpThetaStars[i].resetCount();
        // get the most popular clusters
        clusterRanker.add(new _RankItem(i, m_hdpThetaStars[i].getMemSize()));
    }
    // collect statistics across users in adaptation data
    _HDPThetaStar theta = null;
    _HDPAdaptStruct user;
    for (int i = 0; i < m_userList.size(); i++) {
        user = (_HDPAdaptStruct) m_userList.get(i);
        for (_Review r : user.getReviews()) {
            if (r.getType() != rType.ADAPTATION)
                // only touch the adaptation data
                continue;
            else {
                theta = r.getHDPThetaStar();
                if (r.getYLabel() == 1)
                    theta.incPosCount();
                else
                    theta.incNegCount();
            }
        }
    }
    System.out.print("[Info]Clusters:");
    for (int i = 0; i < m_kBar; i++) System.out.format("%s\t", m_hdpThetaStars[i].showStat());
    if (m_features == null)
        System.out.print(String.format("\n[Info]%d Clusters are found in total!\n", m_kBar));
    else if (printDetails) {
        System.out.print(String.format("\n[Info]%d Clusters are found in total! And the highligt is as follows\n", m_kBar));
        accumulateFeatureCount();
        for (_RankItem it : clusterRanker) printTopWords(m_hdpThetaStars[it.m_index]);
    }
}

Example 65 with structures._RankItem

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

the class DCMLDA method printTopWords.

@Override
public void printTopWords(int k, String betaFile) {
    double logLikelihood = calculate_log_likelihood();
    System.out.format("final log likelihood %.3f\t", logLikelihood);
    System.out.println("TopWord FilePath:" + betaFile);
    Arrays.fill(m_sstat, 0);
    for (_Doc d : m_trainSet) {
        for (int i = 0; i < number_of_topics; i++) m_sstat[i] += m_logSpace ? Math.exp(d.m_topics[i]) : d.m_topics[i];
    }
    Utils.L1Normalization(m_sstat);
    try {
        PrintWriter topWordWriter = new PrintWriter(new File(betaFile));
        for (int i = 0; i < m_beta.length; i++) {
            MyPriorityQueue<_RankItem> fVector = new MyPriorityQueue<_RankItem>(k);
            for (int j = 0; j < vocabulary_size; j++) fVector.add(new _RankItem(m_corpus.getFeature(j), m_beta[i][j]));
            topWordWriter.format("Topic %d(%.5f):\t", i, m_sstat[i]);
            for (_RankItem it : fVector) topWordWriter.format("%s(%.5f)\t", it.m_name, m_logSpace ? Math.exp(it.m_value) : it.m_value);
            topWordWriter.write("\n");
        }
        topWordWriter.close();
    } catch (Exception ex) {
        System.err.print("File Not Found");
    }
}