Java tutorial
/* * LensKit, an open-source toolkit for recommender systems. * Copyright 2014-2017 LensKit contributors (see CONTRIBUTORS.md) * Copyright 2010-2014 Regents of the University of Minnesota * * Permission is hereby granted, free of charge, to any person obtaining * a copy of this software and associated documentation files (the * "Software"), to deal in the Software without restriction, including * without limitation the rights to use, copy, modify, merge, publish, * distribute, sublicense, and/or sell copies of the Software, and to * permit persons to whom the Software is furnished to do so, subject to * the following conditions: * * The above copyright notice and this permission notice shall be * included in all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ package org.lenskit.pf; import it.unimi.dsi.fastutil.longs.LongIterator; import it.unimi.dsi.fastutil.longs.LongIterators; import org.apache.commons.math3.linear.RealVector; import org.lenskit.api.Result; import org.lenskit.api.ResultMap; import org.lenskit.basic.AbstractItemScorer; import org.lenskit.results.Results; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import javax.annotation.Nonnull; import javax.inject.Inject; import java.util.ArrayList; import java.util.Collection; import java.util.List; public class HPFItemScorer extends AbstractItemScorer { private static Logger logger = LoggerFactory.getLogger(HPFItemScorer.class); private final HPFModel model; private final boolean isProbPrediction; @Inject public HPFItemScorer(HPFModel mod, @IsProbabilityPrediction boolean probPred) { model = mod; isProbPrediction = probPred; } @Nonnull @Override public ResultMap scoreWithDetails(long user, @Nonnull Collection<Long> items) { RealVector uvec = model.getUserVector(user); if (uvec == null) { return Results.newResultMap(); } List<Result> results = new ArrayList<>(items.size()); LongIterator iter = LongIterators.asLongIterator(items.iterator()); while (iter.hasNext()) { long item = iter.nextLong(); RealVector ivec = model.getItemVector(item); if (ivec != null) { double score = uvec.dotProduct(ivec); if (isProbPrediction) { score = 1 - Math.exp(-score); } results.add(Results.create(item, score)); } } return Results.newResultMap(results); } }