void FTSSpec::_scoreStringV2( const Tools& tools,
StringData raw,
TermFrequencyMap* docScores,
double weight ) const {
ScoreHelperMap terms;
unsigned numTokens = 0;
Tokenizer i( tools.language, raw );
while ( i.more() ) {
Token t = i.next();
if ( t.type != Token::TEXT )
continue;
string term = t.data.toString();
makeLower( &term );
if ( tools.stopwords->isStopWord( term ) ) {
continue;
}
term = tools.stemmer->stem( term );
ScoreHelperStruct& data = terms[term];
if ( data.exp ) {
data.exp *= 2;
}
else {
data.exp = 1;
}
data.count += 1;
data.freq += ( 1 / data.exp );
numTokens++;
}
for ( ScoreHelperMap::const_iterator i = terms.begin(); i != terms.end(); ++i ) {
const string& term = i->first;
const ScoreHelperStruct& data = i->second;
// in order to adjust weights as a function of term count as it
// relates to total field length. ie. is this the only word or
// a frequently occuring term? or does it only show up once in
// a long block of text?
double coeff = ( 0.5 * data.count / numTokens ) + 0.5;
// if term is identical to the raw form of the
// field (untokenized) give it a small boost.
double adjustment = 1;
if ( raw.size() == term.length() && raw.equalCaseInsensitive( term ) )
adjustment += 0.1;
double& score = (*docScores)[term];
score += ( weight * data.freq * coeff * adjustment );
verify( score <= MAX_WEIGHT );
}
}
std::set<std::string> DatabaseHolderImpl::_getNamesWithConflictingCasing_inlock(StringData name) {
std::set<std::string> duplicates;
for (const auto& nameAndPointer : _dbs) {
// A name that's equal with case-insensitive match must be identical, or it's a duplicate.
if (name.equalCaseInsensitive(nameAndPointer.first) && name != nameAndPointer.first)
duplicates.insert(nameAndPointer.first);
}
return duplicates;
}
void FTSSpec::_scoreStringV2(FTSTokenizer* tokenizer,
StringData raw,
TermFrequencyMap* docScores,
double weight) const {
ScoreHelperMap terms;
unsigned numTokens = 0;
tokenizer->reset(raw.rawData(), FTSTokenizer::kFilterStopWords);
while (tokenizer->moveNext()) {
StringData term = tokenizer->get();
ScoreHelperStruct& data = terms[term];
if (data.exp) {
data.exp *= 2;
} else {
data.exp = 1;
}
data.count += 1;
data.freq += (1 / data.exp);
numTokens++;
}
for (ScoreHelperMap::const_iterator i = terms.begin(); i != terms.end(); ++i) {
const string& term = i->first;
const ScoreHelperStruct& data = i->second;
// in order to adjust weights as a function of term count as it
// relates to total field length. ie. is this the only word or
// a frequently occuring term? or does it only show up once in
// a long block of text?
double coeff = (0.5 * data.count / numTokens) + 0.5;
// if term is identical to the raw form of the
// field (untokenized) give it a small boost.
double adjustment = 1;
if (raw.size() == term.length() && raw.equalCaseInsensitive(term))
adjustment += 0.1;
double& score = (*docScores)[term];
score += (weight * data.freq * coeff * adjustment);
verify(score <= MAX_WEIGHT);
}
}
