/*
* LensKit, an open source recommender systems toolkit.
* Copyright 2010-2014 LensKit Contributors. See CONTRIBUTORS.md.
* Work on LensKit has been funded by the National Science Foundation under
* grants IIS 05-34939, 08-08692, 08-12148, and 10-17697.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2.1 of the
* License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
* details.
*
* You should have received a copy of the GNU General Public License along with
* this program; if not, write to the Free Software Foundation, Inc., 51
* Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
package org.grouplens.lenskit.knn.item;
import it.unimi.dsi.fastutil.longs.LongSortedSet;
import org.grouplens.lenskit.basic.AbstractGlobalItemScorer;
import org.grouplens.lenskit.collections.LongUtils;
import org.grouplens.lenskit.knn.item.model.ItemItemModel;
import org.grouplens.lenskit.vectors.MutableSparseVector;
import javax.annotation.Nonnull;
import javax.inject.Inject;
import java.util.Collection;
/**
* Score items based on the basket of items using an item-item CF model.
*
* @author <a href="http://www.grouplens.org">GroupLens Research</a>
*/
public class ItemItemGlobalScorer extends AbstractGlobalItemScorer {
protected final ItemItemModel model;
@Nonnull
protected final
NeighborhoodScorer scorer;
@Nonnull
protected final
ItemScoreAlgorithm algorithm;
@Inject
public ItemItemGlobalScorer(ItemItemModel m, ItemScoreAlgorithm algo) {
model = m;
// The global item scorer use the SimilaritySumNeighborhoodScorer for the unary ratings
this.scorer = new SimilaritySumNeighborhoodScorer();
algorithm = algo;
}
@Override
public void globalScore(@Nonnull Collection<Long> queryItems,
@Nonnull MutableSparseVector output) {
// create the unary rating for the items
LongSortedSet qItems = LongUtils.packedSet(queryItems);
MutableSparseVector basket = MutableSparseVector.create(qItems, 1.0);
output.clear();
algorithm.scoreItems(model, basket, output, scorer);
}
}