org.lenskit.cli.commands.Recommend Maven / Gradle / Ivy
/*
* 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 GroupLens Research
*/
@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 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);
}
}
}
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