/*
* 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.slopeone;
import it.unimi.dsi.fastutil.longs.Long2ObjectMap;
import it.unimi.dsi.fastutil.longs.Long2ObjectOpenHashMap;
import it.unimi.dsi.fastutil.longs.LongIterator;
import it.unimi.dsi.fastutil.longs.LongSet;
import org.apache.commons.lang3.tuple.Pair;
import org.grouplens.lenskit.data.dao.ItemDAO;
import org.grouplens.lenskit.vectors.*;
import java.util.Map;
public class SlopeOneModelDataAccumulator {
private Long2ObjectMap<MutableSparseVector> workMatrix;
private double damping;
/**
* Creates an accumulator to process rating data and generate the necessary data for
* a {@code SlopeOneItemScorer}.
*
* @param damping A damping term for deviation calculations.
* @param dao The DataAccessObject interfacing with the data for the model
*/
public SlopeOneModelDataAccumulator(double damping, ItemDAO dao) {
this.damping = damping;
LongSet items = dao.getItemIds();
workMatrix = new Long2ObjectOpenHashMap<MutableSparseVector>(items.size());
LongIterator iter = items.iterator();
while (iter.hasNext()) {
long item = iter.nextLong();
workMatrix.put(item, MutableSparseVector.create(items));
workMatrix.get(item).addChannelVector(SlopeOneModel.CORATINGS_SYMBOL);
}
}
/**
* Puts the item pair into the accumulator.
*
* @param id1 The id of the first item.
* @param itemVec1 The rating vector of the first item.
* @param id2 The id of the second item.
* @param itemVec2 The rating vector of the second item.
*/
public void putItemPair(long id1, SparseVector itemVec1, long id2, SparseVector itemVec2) {
if (workMatrix == null) {
throw new IllegalStateException("Model is already built");
}
// to profit from matrix symmetry, always store by the lesser id
if (id1 < id2) {
int coratings = 0;
double deviation = 0.0;
for (Pair<VectorEntry,VectorEntry> pair: Vectors.fastIntersect(itemVec1, itemVec2)) {
coratings++;
deviation += pair.getLeft().getValue() - pair.getRight().getValue();
}
deviation = (coratings == 0) ? Double.NaN : deviation;
workMatrix.get(id1).set(id2, deviation);
workMatrix.get(id1).getChannelVector(SlopeOneModel.CORATINGS_SYMBOL).set(id2, coratings);
}
}
/**
* @return A matrix of item deviation and corating values to be used by
* a {@code SlopeOneItemScorer}.
*/
public Long2ObjectMap<ImmutableSparseVector> buildMatrix() {
if (workMatrix == null) {
throw new IllegalStateException("Model is already built");
}
Long2ObjectMap<ImmutableSparseVector> matrix =
new Long2ObjectOpenHashMap<ImmutableSparseVector>(workMatrix.size());
for (MutableSparseVector vec : workMatrix.values()) {
for (VectorEntry e : vec) {
double deviation = e.getValue();
int coratings = (int)vec.getChannelVector(SlopeOneModel.CORATINGS_SYMBOL).get(e);
vec.set(e, deviation/(coratings + damping));
}
}
for (Map.Entry<Long, MutableSparseVector> e : workMatrix.entrySet()) {
matrix.put(e.getKey(), e.getValue().freeze());
}
workMatrix = null;
return matrix;
}
}