void expandQueryByMap(std::map<int,double>& fb, double origModCoeff) {
if (!qm) {
qm = new lemur::api::IndexedRealVector();
} else {
qm->clear();
}
cout << "stage 1" << endl;
debug();
std::map<int,double>::iterator it;
for(it=fb.begin();it!=fb.end();++it)
{
int termID = it->first;
IndexedReal entry;
if(!include(termID)) {
entry.ind = termID;
entry.val = 0;
qm->push_back(entry);
}
}
cout << "stage 2" << endl;
debug();
// get original query term count
double countSum = totalCount();
startIteration();
while (hasMore()) {
lemur::api::QueryTerm *qt = nextTerm();
setCount(qt->id(), qt->weight()*origModCoeff/countSum);
delete qt;
}
cout << "stage 3" << endl;
debug();
for(it=fb.begin();it!=fb.end();++it)
{
int termID = it->first;
double score = it->second;
incCount(termID, score*(1.0-origModCoeff));
}
cout << "stage 4" << endl;
debug();
//Sum w in Q qtf * log(qtcf/termcount);
colQLikelihood = 0;
colQueryLikelihood();
colKLComputed = false;
}
void expandQuery(MyQueryModel &exRep, double origModCoeff) {
if (!qm) {
qm = new lemur::api::IndexedRealVector();
} else {
qm->clear();
}
// get original query term count
double countSum = totalCount();
// add expand query's term, init weight as zero
exRep.startIteration();
while (exRep.hasMore()) {
lemur::api::QueryTerm *qt = exRep.nextTerm();
IndexedReal entry;
if(!include(qt->id())) {
entry.ind = qt->id();
//entry.val = qt->weight();
entry.val = 0;
qm->push_back(entry);
}
delete qt;
}
qm->Sort();
// cout << "after push words" << endl;
// cout << "original total count = " << totalCount() << endl;
// debug();
// discounting the original model
startIteration();
while (hasMore()) {
lemur::api::QueryTerm *qt = nextTerm();
setCount(qt->id(), qt->weight()*origModCoeff/countSum);
delete qt;
}
// debug();
// now adding the new model
double exCountSum = exRep.totalCount();
exRep.startIteration();
while (exRep.hasMore()) {
lemur::api::QueryTerm *qt = exRep.nextTerm();
incCount(qt->id(), qt->weight()*(1.0-origModCoeff)/exCountSum);
delete qt;
}
debug();
//Sum w in Q qtf * log(qtcf/termcount);
colQLikelihood = 0;
colQueryLikelihood();
colKLComputed = false;
}
void
ears::DoubleDocUnigramCounter::countDocUnigram( lemur::api::DOCID_T docID,
double weight )
{
lemur::api::TermInfoList *tList = ind.termInfoList( docID );
const lemur::api::TermInfo *info;
tList->startIteration();
while ( tList->hasMore() ) {
info = tList->nextEntry();
incCount( info->termID(), weight*info->count() );
}
delete tList;
}
void interpolateWith(const lemur::langmod::UnigramLM &qModel,
double origModCoeff,
int howManyWord,
double prSumThresh,
double prThresh) {
if (!qm) {
qm = new lemur::api::IndexedRealVector();
} else {
qm->clear();
}
qModel.startIteration();
while (qModel.hasMore()) {
IndexedReal entry;
qModel.nextWordProb((TERMID_T &)entry.ind,entry.val);
qm->push_back(entry);
}
qm->Sort();
double countSum = totalCount();
startIteration();
while (hasMore()) {
QueryTerm *qt = nextTerm();
setCount(qt->id(), qt->weight()*origModCoeff/countSum);
delete qt;
}
cout << "-------- FB terms --------" << endl;
double prSum = 0;
int wdCount = 0;
IndexedRealVector::iterator it;
it = qm->begin();
while (it != qm->end() && prSum < prSumThresh &&
wdCount < howManyWord && (*it).val >=prThresh) {
incCount((*it).ind, (*it).val*(1-origModCoeff));
cout << ind.term(it->ind) << endl;
prSum += (*it).val;
it++;
wdCount++;
}
cout << "--------------------------" << endl;
colQLikelihood = 0;
colQueryLikelihood();
colKLComputed = false;
}
