Mahout之UserCF-优快云博客

本文介绍了一个基于用户协同过滤的推荐系统实现方法，利用Pearson相关系数相似性度量来计算用户之间的相似性，并通过最近邻算法为用户提供个性化推荐。

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package com.recommand.engine;

import com.math.Cmd;
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.CachingRecommender;
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.model.JDBCDataModel;
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 PSHalpUserCF {
    private  String m_strFileName ; 
    private DataModel m_dataModel ;
    private Recommender m_recommender;
    public PSHalpUserCF(String str ) throws IOException {
        m_strFileName = str ; 
        m_dataModel = new FileDataModel(new File(m_strFileName )); 
    }
    public DataModel GetDataModel(){
        return m_dataModel ; 
    }

    public void Parse() throws TasteException {
        UserSimilarity userSimilarity = new PearsonCorrelationSimilarity(m_dataModel);

        UserNeighborhood userNeighborhood = new NearestNUserNeighborhood(2,
        userSimilarity, m_dataModel);

        m_recommender = new GenericUserBasedRecommender(m_dataModel,
        userNeighborhood, userSimilarity);
    }

    public void GetRecommender ( int which , int range ) throws TasteException  {

        for( RecommendedItem x : m_recommender.recommend(which ,  range )  ){
            System.out.println( x ); 
        }
    }

    public int GetUserCountFromDataModel( ) {   
        Cmd pcmd=new Cmd();
        String str = "./sh//usercount.sh " +   m_strFileName ; 
        //System.out.println(str  ) ; 
        List<String> res = pcmd.exec( str ) ;
        if( res.size() > 0 ){
            return Integer.parseInt(  res.get( 0 ) ) ;
        }
        return -1  ; 
    }
}