org.lenskit.cli.commands.Recommend.java Source code

Introduction

Here is the source code for org.lenskit.cli.commands.Recommend.java

Source

/*
 * 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.inf.ArgumentParser;
import net.sourceforge.argparse4j.inf.Namespace;
import org.lenskit.api.RecommenderBuildException;
import org.lenskit.data.dao.ItemNameDAO;
import org.lenskit.LenskitRecommender;
import org.lenskit.LenskitRecommenderEngine;
import org.lenskit.api.ItemRecommender;
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.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.IOException;
import java.util.List;

/**
 * Generate Top-N recommendations for users.
 *
 * @since 2.1
 * @author <a href="http://www.grouplens.org">GroupLens Research</a>
 */
@AutoService(Command.class)
public class Recommend implements Command {
    private final Logger logger = LoggerFactory.getLogger(Recommend.class);

    @Override
    public String getName() {
        return "recommend";
    }

    @Override
    public String getHelp() {
        return "generate recommendations for users";
    }

    @Override
    public void execute(Namespace opts) throws IOException, RecommenderBuildException {
        Context ctx = new Context(opts);
        LenskitRecommenderEngine engine = ctx.loader.loadEngine();

        List<Long> users = ctx.options.get("users");
        final int n = ctx.options.getInt("num_recs");

        try (LenskitRecommender rec = engine.createRecommender()) {
            ItemRecommender irec = rec.getItemRecommender();
            ItemNameDAO indao = rec.get(ItemNameDAO.class);
            if (irec == null) {
                logger.error("recommender has no item recommender");
                throw new UnsupportedOperationException("no item recommender");
            }

            logger.info("recommending for {} users", users.size());
            Stopwatch timer = Stopwatch.createStarted();
            for (long user : users) {
                ResultList recs = irec.recommendWithDetails(user, n, null, null);
                System.out.format("recommendations for user %d:%n", user);
                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 for {} users in {}", users.size(), timer);
        }
    }

    public void configureArguments(ArgumentParser parser) {
        parser.description("Generates recommendations for a user.");
        InputData.configureArguments(parser);
        ScriptEnvironment.configureArguments(parser);
        RecommenderLoader.configureArguments(parser);
        parser.addArgument("-n", "--num-recs").type(Integer.class).setDefault(10).metavar("N")
                .help("generate up to N recommendations per user");
        parser.addArgument("users").type(Long.class).nargs("+").metavar("USER").help("recommend for USERS");
    }

    private static class Context {
        private final Namespace options;
        private final InputData input;
        private final ScriptEnvironment environment;
        private final RecommenderLoader loader;

        public Context(Namespace opts) {
            options = opts;
            environment = new ScriptEnvironment(opts);
            input = new InputData(environment, opts);
            loader = new RecommenderLoader(input, environment, opts);
        }
    }
}