void recommender_base::complete_row(const common::sfv_t& query,
common::sfv_t& ret) const {
ret.clear();
vector<pair<string, float> > ids;
similar_row(query, ids, complete_row_similar_num_);
if (ids.size() == 0) {
return;
}
size_t exist_row_num = 0;
sparse_matrix_storage_mixable::model_ptr model = orig_->get_model();
for (size_t i = 0; i < ids.size(); ++i) {
common::sfv_t row;
model->get_row(ids[i].first, row);
if (row.size() == 0) {
continue;
} else {
++exist_row_num;
}
for (size_t j = 0; j < row.size(); ++j) {
ret.push_back(make_pair(row[j].first, row[j].second));
}
}
if (exist_row_num == 0) {
return;
}
common::sort_and_merge(ret);
for (size_t i = 0; i < ret.size(); ++i) {
ret[i].second /= exist_row_num;
}
}
void recommender_base::similar_row(
const std::string& id, std::vector<std::pair<std::string, float> >& ids,
size_t ret_num) const {
ids.clear();
common::sfv_t sfv;
orig_->get_model()->get_row(id, sfv);
similar_row(sfv, ids, ret_num);
}
void lsh::neighbor_row(
const common::sfv_t& query,
vector<pair<string, float> >& ids,
size_t ret_num) const {
similar_row(query, ids, ret_num);
for (size_t i = 0; i < ids.size(); ++i) {
ids[i].second = 1 - ids[i].second;
}
}
void euclid_lsh::neighbor_row(
const string& id,
vector<pair<string, float> >& ids,
size_t ret_num) const {
similar_row(id, ids, ret_num);
for (size_t i = 0; i < ids.size(); ++i) {
ids[i].second = -ids[i].second;
}
}
void bit_index_storage::similar_row(
const std::string& id,
vector<pair<string, float> >& ids,
uint64_t ret_num) const {
ids.clear();
bit_table_t::const_iterator it = bitvals_diff_.find(id);
if (it == bitvals_diff_.end()) {
it = bitvals_.find(id);
if (it == bitvals_.end()) {
return;
}
}
similar_row(it->second, ids, ret_num);
}
