SpringBoot项目使用协同过滤的实现

　　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.EuclideanDistanceSimilarity;

　　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.UserBasedRecommender;

　　import org.apache.mahout.cf.taste.similarity.UserSimilarity;

　　import java.io.File;

　　import java.io.IOException;

　　import java.util.List;

　　public class RecommendationService {

　　private UserBasedRecommender recommender;

　　public RecommendationService() {

　　try {

　　// 加载评分数据文件

　　DataModel model = new FileDataModel(new File("ratings.csv"));

　　// 构建用户相似度计算器

　　UserSimilarity similarity = new EuclideanDistanceSimilarity(model);

　　// 构建用户邻居关系

　　UserNeighborhood neighborhood = new NearestNUserNeighborhood(3, similarity, model);

　　// 构建基于用户的推荐器

　　recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);

　　} catch (IOException | TasteException e) {

　　e.printStackTrace();

　　}

　　}

　　public List getRecommendations(long userId, int numItems) throws TasteException {

　　// 生成推荐结果

　　return recommender.recommend(userId, numItems);

　　}

　　}