use of structures._ChildDoc4BaseWithPhi in project IR_Base by Linda-sunshine.
the class ParentChildAnalyzer method loadChildDoc.
public void loadChildDoc(String fileName) {
if (fileName == null || fileName.isEmpty())
return;
JSONObject json = LoadJSON(fileName);
String content = Utils.getJSONValue(json, "content");
String name = Utils.getJSONValue(json, "name");
String parent = Utils.getJSONValue(json, "parent");
String title = Utils.getJSONValue(json, "title");
//
// _ChildDoc4BaseWithPhi d = new _ChildDoc4BaseWithPhi(m_corpus.getSize(),
// name, "", content, 0);
// _ChildDoc4BaseWithPhi_Hard d = new _ChildDoc4BaseWithPhi_Hard(m_corpus.getSize(), name, "", content, 0) ;
// _ChildDoc4ChildPhi d = new _ChildDoc4ChildPhi(m_corpus.getSize(),
// name,
// "", content, 0);
// _ChildDoc4TwoPhi d = new _ChildDoc4TwoPhi(m_corpus.getSize(), name, "", content, 0);
// _ChildDoc4ThreePhi d = new _ChildDoc4ThreePhi(m_corpus.getSize(), name,
// "", content, 0);
// _ChildDoc4OneTopicProportion d = new _ChildDoc4OneTopicProportion(m_corpus.getSize(), name, "", content, 0);
_ChildDoc d = new _ChildDoc(m_corpus.getSize(), name, "", content, 0);
if (parentHashMap.containsKey(parent)) {
if (AnalyzeDoc(d)) {
// this is a valid child document
// if (parentHashMap.containsKey(parent)) {
_ParentDoc pDoc = parentHashMap.get(parent);
d.setParentDoc(pDoc);
pDoc.addChildDoc(d);
} else {
// System.err.format("filtering comments %s!\n", parent);
}
} else {
// System.err.format("[Warning]Missing parent document %s!\n", parent);
}
}
use of structures._ChildDoc4BaseWithPhi in project IR_Base by Linda-sunshine.
the class ACCTM_C method collectChildStats.
@Override
protected void collectChildStats(_Doc d) {
_ChildDoc4BaseWithPhi cDoc = (_ChildDoc4BaseWithPhi) d;
_ParentDoc pDoc = cDoc.m_parentDoc;
double pDocTopicSum = Utils.sumOfArray(pDoc.m_sstat);
for (int k = 0; k < this.number_of_topics; k++) cDoc.m_xTopics[0][k] += cDoc.m_xTopicSstat[0][k] + d_alpha + cDoc.getMu() * pDoc.m_sstat[k] / pDocTopicSum;
for (int x = 0; x < m_gamma.length; x++) cDoc.m_xProportion[x] += m_gamma[x] + cDoc.m_xSstat[x];
for (int w = 0; w < vocabulary_size; w++) cDoc.m_xTopics[1][w] += cDoc.m_xTopicSstat[1][w];
for (_Word w : d.getWords()) {
w.collectXStats();
}
}
use of structures._ChildDoc4BaseWithPhi in project IR_Base by Linda-sunshine.
the class ACCTM_C method initialize_probability.
protected void initialize_probability(Collection<_Doc> collection) {
createSpace();
for (int i = 0; i < number_of_topics; i++) Arrays.fill(word_topic_sstat[i], d_beta);
Arrays.fill(m_sstat, d_beta * vocabulary_size);
for (_Doc d : collection) {
if (d instanceof _ParentDoc) {
d.setTopics4Gibbs(number_of_topics, 0);
for (_Stn stnObj : d.getSentences()) stnObj.setTopicsVct(number_of_topics);
} else if (d instanceof _ChildDoc4BaseWithPhi) {
((_ChildDoc4BaseWithPhi) d).createXSpace(number_of_topics, m_gamma.length, vocabulary_size, d_beta);
((_ChildDoc4BaseWithPhi) d).setTopics4Gibbs(number_of_topics, 0);
computeMu4Doc((_ChildDoc) d);
}
if (d instanceof _ParentDoc) {
for (_Word w : d.getWords()) {
word_topic_sstat[w.getTopic()][w.getIndex()]++;
m_sstat[w.getTopic()]++;
}
} else if (d instanceof _ChildDoc4BaseWithPhi) {
for (_Word w : d.getWords()) {
int xid = w.getX();
int tid = w.getTopic();
int wid = w.getIndex();
// update global
if (xid == 0) {
word_topic_sstat[tid][wid]++;
m_sstat[tid]++;
}
}
}
}
imposePrior();
m_statisticsNormalized = false;
}
use of structures._ChildDoc4BaseWithPhi in project IR_Base by Linda-sunshine.
the class ACCTM_C method calculate_log_likelihood4Child.
@Override
protected double calculate_log_likelihood4Child(_Doc d) {
_ChildDoc4BaseWithPhi cDoc = (_ChildDoc4BaseWithPhi) d;
double docLogLikelihood = 0.0;
double gammaLen = Utils.sumOfArray(m_gamma);
double cDocXSum = Utils.sumOfArray(cDoc.m_xSstat);
// prepare compute the normalizers
_SparseFeature[] fv = cDoc.getSparse();
for (int i = 0; i < fv.length; i++) {
int wid = fv[i].getIndex();
double value = fv[i].getValue();
double wordLogLikelihood = 0;
for (int k = 0; k < number_of_topics; k++) {
double wordPerTopicLikelihood = childWordByTopicProb(k, wid) * childTopicInDocProb(k, cDoc) * childXInDocProb(0, cDoc) / (cDocXSum + gammaLen);
wordLogLikelihood += wordPerTopicLikelihood;
}
double wordPerTopicLikelihood = childLocalWordByTopicProb(wid, cDoc) * childXInDocProb(1, cDoc) / (cDocXSum + gammaLen);
wordLogLikelihood += wordPerTopicLikelihood;
if (Math.abs(wordLogLikelihood) < 1e-10) {
System.out.println("wordLoglikelihood\t" + wordLogLikelihood);
wordLogLikelihood += 1e-10;
}
wordLogLikelihood = Math.log(wordLogLikelihood);
docLogLikelihood += value * wordLogLikelihood;
}
return docLogLikelihood;
}
use of structures._ChildDoc4BaseWithPhi in project IR_Base by Linda-sunshine.
the class ACCTM_C method sampleInChildDoc.
protected void sampleInChildDoc(_Doc d) {
_ChildDoc4BaseWithPhi cDoc = (_ChildDoc4BaseWithPhi) d;
int wid, tid, xid;
double normalizedProb;
for (_Word w : cDoc.getWords()) {
wid = w.getIndex();
tid = w.getTopic();
xid = w.getX();
if (xid == 0) {
cDoc.m_xTopicSstat[xid][tid]--;
cDoc.m_xSstat[xid]--;
cDoc.m_wordXStat.put(wid, cDoc.m_wordXStat.get(wid) - 1);
if (m_collectCorpusStats) {
word_topic_sstat[tid][wid]--;
m_sstat[tid]--;
}
} else if (xid == 1) {
cDoc.m_xTopicSstat[xid][wid]--;
cDoc.m_xSstat[xid]--;
cDoc.m_childWordSstat--;
}
normalizedProb = 0;
double pLambdaZero = childXInDocProb(0, cDoc);
double pLambdaOne = childXInDocProb(1, cDoc);
for (tid = 0; tid < number_of_topics; tid++) {
double pWordTopic = childWordByTopicProb(tid, wid);
double pTopic = childTopicInDocProb(tid, cDoc);
m_topicProbCache[tid] = pWordTopic * pTopic * pLambdaZero;
normalizedProb += m_topicProbCache[tid];
}
double pWordTopic = childLocalWordByTopicProb(wid, cDoc);
m_topicProbCache[tid] = pWordTopic * pLambdaOne;
normalizedProb += m_topicProbCache[tid];
normalizedProb *= m_rand.nextDouble();
for (tid = 0; tid < m_topicProbCache.length; tid++) {
normalizedProb -= m_topicProbCache[tid];
if (normalizedProb <= 0)
break;
}
if (tid == m_topicProbCache.length)
tid--;
if (tid < number_of_topics) {
xid = 0;
w.setX(xid);
w.setTopic(tid);
cDoc.m_xTopicSstat[xid][tid]++;
cDoc.m_xSstat[xid]++;
if (cDoc.m_wordXStat.containsKey(wid)) {
cDoc.m_wordXStat.put(wid, cDoc.m_wordXStat.get(wid) + 1);
} else {
cDoc.m_wordXStat.put(wid, 1);
}
if (m_collectCorpusStats) {
word_topic_sstat[tid][wid]++;
m_sstat[tid]++;
}
} else if (tid == (number_of_topics)) {
xid = 1;
w.setX(xid);
w.setTopic(tid);
cDoc.m_xTopicSstat[xid][wid]++;
cDoc.m_xSstat[xid]++;
cDoc.m_childWordSstat++;
}
}
}
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