您的位置:首页 > 其它

[mahout in action] 调通第一个例子

2014-09-25 19:49 375 查看
第一个例子是给出了5个用户对物品的评分,基于用户的协同过滤,采用Pearson相似度来找到最相近的用户,并提供推荐。

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

import org.apache.mahout.cf.taste.common.TasteException;
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;

public class RecommenderIntro {

public static void main(String[] args) throws IOException, TasteException {
DataModel model = new FileDataModel(new File("./data/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);
}
}

}


程序输出

14/09/25 19:47:01 INFO file.FileDataModel: Creating FileDataModel for file .\data\intro.csv
14/09/25 19:47:01 INFO file.FileDataModel: Reading file info...
14/09/25 19:47:01 INFO file.FileDataModel: Read lines: 21
14/09/25 19:47:01 INFO model.GenericDataModel: Processed 5 users
RecommendedItem[item:104, value:4.257081]
内容来自用户分享和网络整理,不保证内容的准确性,如有侵权内容,可联系管理员处理 点击这里给我发消息
标签: