/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.cf.taste.similarity.precompute.example;
import org.apache.mahout.cf.taste.example.grouplens.GroupLensDataModel;
import org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity;
import org.apache.mahout.cf.taste.impl.similarity.precompute.FileSimilarItemsWriter;
import org.apache.mahout.cf.taste.impl.similarity.precompute.MultithreadedBatchItemSimilarities;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.recommender.ItemBasedRecommender;
import org.apache.mahout.cf.taste.similarity.precompute.BatchItemSimilarities;
import java.io.File;
/**
* Example that precomputes all item similarities of the Movielens1M dataset
*
* Usage: download movielens1M from http://www.grouplens.org/node/73 , unzip it and invoke this code with the path
* to the ratings.dat file as argument
*
*/
public final class BatchItemSimilaritiesGroupLens {
private BatchItemSimilaritiesGroupLens() {}
public static void main(String[] args) throws Exception {
if (args.length != 1) {
System.err.println("Need path to ratings.dat of the movielens1M dataset as argument!");
System.exit(-1);
}
File resultFile = new File(System.getProperty("java.io.tmpdir"), "similarities.csv");
if (resultFile.exists()) {
resultFile.delete();
}
DataModel dataModel = new GroupLensDataModel(new File(args[0]));
ItemBasedRecommender recommender = new GenericItemBasedRecommender(dataModel,
new LogLikelihoodSimilarity(dataModel));
BatchItemSimilarities batch = new MultithreadedBatchItemSimilarities(recommender, 5);
int numSimilarities = batch.computeItemSimilarities(Runtime.getRuntime().availableProcessors(), 1,
new FileSimilarItemsWriter(resultFile));
System.out.println("Computed " + numSimilarities + " similarities for " + dataModel.getNumItems() + " items "
+ "and saved them to " + resultFile.getAbsolutePath());
}
}