SpringBoot项目使用协同过滤的实现

<dependencies>
    <dependency>
        <groupId>org.apache.mahout</groupId>
        <artifactId>mahout-core</artifactId>
        <version>0.13.0</version>
    </dependency>
    <dependency>
        <groupId>org.apache.mahout</groupId>
        <artifactId>mahout-integration</artifactId>
        <version>0.13.0</version>
    </dependency>
</dependencies>

userId,itemId,rating
1,101,5
1,102,4
2,101,2
2,103,3
3,102,5
3,103,4

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<RecommendedItem> getRecommendations(long userId, int numItems) throws TasteException {
        // 生成推荐结果
        return recommender.recommend(userId, numItems);
    }
}

import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import java.util.List;
@RestController
@RequestMapping("/recommend")
public class RecommendationController {
    private RecommendationService recommendationService;
    public RecommendationController(RecommendationService recommendationService) {
        this.recommendationService = recommendationService;
    }
    @GetMapping("/{userId}/{numItems}")
    public List<RecommendedItem> recommendItems(@PathVariable long userId, @PathVariable int numItems) throws TasteException {
        return recommendationService.getRecommendations(userId, numItems);
    }
}

import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import java.util.List;
public class RecommendationTest {
    public static void main(String[] args) throws TasteException {
        RecommendationService recommendationService = new RecommendationService();
        // 获取用户1的3个推荐物品
        List<RecommendedItem> recommendations = recommendationService.getRecommendations(1, 3);
        // 打印推荐结果
        for (RecommendedItem item : recommendations) {
            System.out.println("Item ID: " + item.getItemID() + ", Score: " + item.getValue());
        }
    }
}