RecommenderIntro.java

package org.mahout.recommendations;

import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
import org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood;
import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import org.apache.mahout.cf.taste.recommender.Recommender;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;

import java.io.File;
import java.util.List;

/**
 * @author Krisztian_Horvath
 */
public class RecommenderIntro {
    public static void main(String[] args) throws Exception {
        DataModel model = new FileDataModel(new File("src/main/resources/intro.csv"));
        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
        UserNeighborhood neighborhood = new NearestNUserNeighborhood(2, similarity, model);
        Recommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
        List<RecommendedItem> recommendations = recommender.recommend(1, 1);
        for (RecommendedItem recommendation : recommendations) {
            System.out.println(recommendation);
        }
    }
}