std::vector<search_result>
ranker::score(inverted_index& idx, const corpus::document& query,
uint64_t num_results /* = 10 */,
const filter_function_type& filter /* return true */)
{
auto counts = idx.tokenize(query);
return score(idx, counts.begin(), counts.end(), num_results, filter);
}
void forward_index::impl::uninvert(const inverted_index& inv_idx)
{
io::compressed_file_reader inv_reader{inv_idx.index_name()
+ idx_->impl_->files[POSTINGS],
io::default_compression_reader_func};
term_id t_id{0};
chunk_handler<forward_index> handler{idx_->index_name()};
{
auto producer = handler.make_producer();
while (inv_reader.has_next())
{
inverted_pdata_type pdata{t_id};
pdata.read_compressed(inv_reader);
producer(pdata.primary_key(), pdata.counts());
++t_id;
}
}
handler.merge_chunks();
compressed_postings_to_libsvm(inv_idx.num_docs());
}
std::vector<std::pair<doc_id, double>>
ranker::score(inverted_index& idx, corpus::document& query,
uint64_t num_results /* = 10 */,
const std::function<bool(doc_id d_id)>& filter /* return true */)
{
if (query.counts().empty())
idx.tokenize(query);
score_data sd{idx, idx.avg_doc_length(),
idx.num_docs(), idx.total_corpus_terms(),
query};
// zeros out elements and (if necessary) resizes the vector; this eliminates
// constructing a new vector each query for the same index
results_.assign(sd.num_docs, std::numeric_limits<double>::lowest());
for (auto& tpair : query.counts())
{
term_id t_id{idx.get_term_id(tpair.first)};
auto pdata = idx.search_primary(t_id);
sd.doc_count = pdata->counts().size();
sd.t_id = t_id;
sd.query_term_count = tpair.second;
sd.corpus_term_count = idx.total_num_occurences(sd.t_id);
for (auto& dpair : pdata->counts())
{
sd.d_id = dpair.first;
sd.doc_term_count = dpair.second;
sd.doc_size = idx.doc_size(dpair.first);
sd.doc_unique_terms = idx.unique_terms(dpair.first);
// if this is the first time we've seen this document, compute
// its initial score
if (results_[dpair.first] == std::numeric_limits<double>::lowest())
results_[dpair.first] = initial_score(sd);
results_[dpair.first] += score_one(sd);
}
}
using doc_pair = std::pair<doc_id, double>;
auto doc_pair_comp = [](const doc_pair& a, const doc_pair& b)
{ return a.second > b.second; };
std::priority_queue<doc_pair,
std::vector<doc_pair>,
decltype(doc_pair_comp)> pq{doc_pair_comp};
for (uint64_t id = 0; id < results_.size(); ++id)
{
if (!filter(doc_id{id}))
continue;
pq.emplace(doc_id{id}, results_[id]);
if (pq.size() > num_results)
pq.pop();
}
std::vector<doc_pair> sorted;
while (!pq.empty())
{
sorted.emplace_back(pq.top());
pq.pop();
}
std::reverse(sorted.begin(), sorted.end());
return sorted;
}
