/* * 这里做的是一个基于用户的Mahout推荐程序* 这里利用已经准备好的数据。* */package byuser;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.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) {// TODO Auto-generated method stubtry {//进行数据的装载DataModel model = new FileDataModel(new File("E:\\mahout项目\\examples\\intro.csv"));UserSimilarity similarity = new org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity(model);UserNeighborhood neighborhood = new NearestNUserNeighborhood(2, similarity, model);//生成推荐引擎Recommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);//为用户已推荐一件商品recommend( , );其中参数的意思是：第几个人，，然后推荐几件商品List<RecommendedItem> recommendations = recommender.recommend(1, 1);for(RecommendedItem recommendation : recommendations){System.out.println("根据您的浏览，为您推荐的商品是：" + recommendation);}} catch (IOException e) {// TODO Auto-generated catch blocke.printStackTrace();} catch (TasteException e) {// TODO Auto-generated catch blocke.printStackTrace();}}}
结果：
尝到你和你在一起的快乐，你是唯一能让我尝到酸甜苦辣的人。
