Java tutorial
/* * 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.lenskit.cli.commands; import com.google.auto.service.AutoService; import com.google.common.base.Stopwatch; import net.sourceforge.argparse4j.impl.Arguments; import net.sourceforge.argparse4j.inf.ArgumentParser; import net.sourceforge.argparse4j.inf.Namespace; import org.lenskit.LenskitRecommender; import org.lenskit.LenskitRecommenderEngine; import org.lenskit.api.ItemBasedItemRecommender; import org.lenskit.api.RecommenderBuildException; import org.lenskit.api.Result; import org.lenskit.api.ResultList; import org.lenskit.cli.Command; import org.lenskit.cli.util.InputData; import org.lenskit.cli.util.RecommenderLoader; import org.lenskit.cli.util.ScriptEnvironment; import org.lenskit.data.dao.ItemNameDAO; import org.lenskit.util.collections.LongUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.File; import java.io.IOException; import java.util.List; /** * Generate Top-N non-personalized recommendations. * * @since 2.2 * @author <a href="http://www.grouplens.org">GroupLens Research</a> */ @AutoService(Command.class) public class GlobalRecommend implements Command { private final Logger logger = LoggerFactory.getLogger(GlobalRecommend.class); @Override public String getName() { return "global-recommend"; } @Override public String getHelp() { return "generate non-personalized recommendations"; } @Override public void execute(Namespace opts) throws IOException, RecommenderBuildException { ScriptEnvironment env = new ScriptEnvironment(opts); InputData input = new InputData(env, opts); RecommenderLoader loader = new RecommenderLoader(input, env, opts); LenskitRecommenderEngine engine = loader.loadEngine(); List<Long> items = opts.get("items"); final int n = opts.getInt("num_recs"); try (LenskitRecommender rec = engine.createRecommender()) { ItemBasedItemRecommender irec = rec.getItemBasedItemRecommender(); ItemNameDAO indao = rec.get(ItemNameDAO.class); if (irec == null) { logger.error("recommender has no global recommender"); throw new UnsupportedOperationException("no global recommender"); } logger.info("using {} reference items: {}", items.size(), items); Stopwatch timer = Stopwatch.createStarted(); ResultList recs = irec.recommendRelatedItemsWithDetails(LongUtils.packedSet(items), n, null, null); for (Result item : recs) { System.out.format("%d", item.getId()); if (indao != null) { System.out.format(" (%s)", indao.getItemName(item.getId())); } System.out.format(": %.3f", item.getScore()); System.out.println(); } timer.stop(); logger.info("recommended in {}", timer); } } public void configureArguments(ArgumentParser parser) { parser.description("Generates non-personalized recommendations using optional reference items."); InputData.configureArguments(parser); ScriptEnvironment.configureArguments(parser); parser.addArgument("-n", "--num-recs").type(Integer.class).setDefault(10).metavar("N") .help("generate up to N recommendations"); parser.addArgument("-c", "--config-file").type(File.class).action(Arguments.append()).metavar("FILE") .help("use configuration from FILE"); parser.addArgument("-m", "--model-file").type(File.class).metavar("FILE").help("load model from FILE"); parser.addArgument("items").type(Long.class).nargs("*").metavar("ITEM") .help("use ITEMS as reference for recommendation"); } }