/*
* 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 org.grouplens.lenskit.ItemScorer;
import org.grouplens.lenskit.basic.AbstractItemScorer;
import org.grouplens.lenskit.data.dao.UserEventDAO;
import org.grouplens.lenskit.data.event.Event;
import org.grouplens.lenskit.data.history.History;
import org.grouplens.lenskit.data.history.UserHistory;
import org.grouplens.lenskit.data.history.UserHistorySummarizer;
import org.grouplens.lenskit.knn.item.model.ItemItemModel;
import org.grouplens.lenskit.symbols.Symbol;
import org.grouplens.lenskit.transform.normalize.UserVectorNormalizer;
import org.grouplens.lenskit.transform.normalize.VectorTransformation;
import org.grouplens.lenskit.vectors.MutableSparseVector;
import org.grouplens.lenskit.vectors.SparseVector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import javax.annotation.Nonnull;
import javax.inject.Inject;
/**
* Score items using an item-item CF model. User ratings are <b>not</b> supplied
* as default preferences.
*
* @author <a href="http://www.grouplens.org">GroupLens Research</a>
*/
public class ItemItemScorer extends AbstractItemScorer implements ItemScorer {
private static final Logger logger = LoggerFactory.getLogger(ItemItemScorer.class);
public static final Symbol NEIGHBORHOOD_SIZE_SYMBOL =
Symbol.of("org.grouplens.lenskit.knn.item.neighborhoodSize");
protected final ItemItemModel model;
private final UserEventDAO dao;
@Nonnull
protected final UserVectorNormalizer normalizer;
protected final UserHistorySummarizer summarizer;
@Nonnull
protected final NeighborhoodScorer scorer;
@Nonnull
protected final ItemScoreAlgorithm algorithm;
/**
* Construct a new item-item scorer.
*
* @param dao The DAO.
* @param m The model
* @param sum The history summarizer.
* @param scorer The neighborhood scorer.
* @param algo The item scoring algorithm. It converts neighborhoods to scores.
*/
@Inject
public ItemItemScorer(UserEventDAO dao, ItemItemModel m,
UserHistorySummarizer sum,
NeighborhoodScorer scorer,
ItemScoreAlgorithm algo,
UserVectorNormalizer norm) {
this.dao = dao;
model = m;
summarizer = sum;
this.scorer = scorer;
algorithm = algo;
normalizer = norm;
logger.debug("configured item-item scorer with scorer {}", scorer);
}
@Nonnull
public UserVectorNormalizer getNormalizer() {
return normalizer;
}
/**
* Score items by computing predicted ratings.
*
* @see ItemScoreAlgorithm#scoreItems(ItemItemModel, SparseVector, MutableSparseVector, NeighborhoodScorer)
*/
@Override
public void score(long user, @Nonnull MutableSparseVector scores) {
UserHistory<? extends Event> history = dao.getEventsForUser(user, summarizer.eventTypeWanted());
if (history == null) {
history = History.forUser(user);
}
SparseVector summary = summarizer.summarize(history);
VectorTransformation transform = normalizer.makeTransformation(user, summary);
MutableSparseVector normed = summary.mutableCopy();
transform.apply(normed);
scores.clear();
algorithm.scoreItems(model, normed, scores, scorer);
// untransform the scores
transform.unapply(scores);
}
}