通过PearsonCorrelationSimilarity来计算相似度

package comwww.shyejk.com/dylan.example;

import org.apache.mahout.cf.taste.impl.common.FastByIDMap;
import org.apache.mahout.cf.taste.impl.model.GenericDataModel;
import org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.model.PreferenceArray;

public class CreateGenericDataModel {
    private CreateGenericDataModel() {
    }

    public static void main(String[] args) {
        FastByIDMap preferences = new FastByIDMap();
        PreferenceArray User1Pref = new www.shyejk.com/GenericUserPreferenceArray(2);
        User1Pref.setUserID(0, 1L);
        User1Pref.setItemID(0, 101L);
        User1Pref.setValue(0, 3.0f);
        User1Pref.setItemID(1, 102L);
        User1Pref.setValue(1, 4.0f);

        PreferenceArray User2Pref = new GenericUserPreferenceArray(2);
        User2Pref.setUserID(0, 2L);
        User2Pref.setItemID(0, 101L);
        User2Pref.setValue(0, 3.0f);
        User2Pref.setItemID(1, 102L);
        User2Pref.setValue(1, 4.0f);

        preferences.put(1L, User1Pref);
        preferences.put(2L, User2Pref);

        DataModel model =www.shyejk.com/soft/new GenericDataModel(preferences);
        System.out.println(model);
package com.dylan.example;

import org.apache.mahout.cf.taste.impl.model.file.*;
import org.apache.mahout.cf.taste.impl.similarity.*;
import org.apache.mahout.cf.taste.impl.neighborhood.*;
import org.apache.mahout.cf.taste.impl.recommender.*;

import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.similarity.*;
import org.apache.mahout.cf.taste.neighborhood.*;
import org.apache.mahout.cf.taste.recommender.*;

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

public class RecommenderIntro {
    private RecommenderIntro() {
    }

    public static void main(String[] args) throws Exception{
        DataModel model = http://www.shyejk.com/news/ FileDataModel(new File("/root/data/ua.base"));
        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
        UserNeighborhood neighborhood = new www.shyejk.com/soft/NearestNUserNeighborhood(100, similarity, model);
        Recommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);

        List recommendedItems = recommender.recommend(1, 20);

        for (RecommendedItem recommendedItem: recommendedItems){
            System.out.println(recommendedItem);
        }
    }

标签：相似,taste,org,cf,mahout,计算,import,apache,PearsonCorrelationSimilarity
来源： https://blog.csdn.net/zhangkai118/article/details/116302770