RecommenderFilterSalaryResult

package org.andy.mymahout.recommendation.job;

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.IOException;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;

import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.eval.RecommenderBuilder;
import org.apache.mahout.cf.taste.impl.common.FastIDSet;
import org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.recommender.IDRescorer;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;

public class RecommenderFilterSalaryResult {

final static int NEIGHBORHOOD_NUM = 2;
final static int RECOMMENDER_NUM = 3;

public static void main(String[] args) throws TasteException, IOException {
String file = "datafile/job/pv.csv";
DataModel dataModel = RecommendFactory.buildDataModelNoPref(file);
RecommenderBuilder rb1 = RecommenderEvaluator.userCityBlock(dataModel);
RecommenderBuilder rb2 = RecommenderEvaluator.itemLoglikelihood(dataModel);

Map<Long, Double> averSalary = getAverSalary("datafile/job/job.csv", dataModel);

LongPrimitiveIterator iter = dataModel.getUserIDs();
while (iter.hasNext()) {
long uid = iter.nextLong();
System.out.print("userCityBlock    =>");
filterSalary(uid, rb1, dataModel, averSalary);
System.out.print("itemLoglikelihood=>");
filterSalary(uid, rb2, dataModel, averSalary);
}
}

public static void filterSalary(long uid, RecommenderBuilder recommenderBuilder, DataModel dataModel, Map<Long, Double> averSalary) throws TasteException, IOException {
Set<Long> jobids = getSalaryJobID(uid, "datafile/job/job.csv", averSalary);
IDRescorer rescorer = new JobRescorer(jobids);
List<RecommendedItem> list = recommenderBuilder.buildRecommender(dataModel).recommend(uid, RECOMMENDER_NUM, rescorer);
RecommendFactory.showItems(uid, list, false);
}

public static Set<Long> getSalaryJobID(long uid, String file, Map<Long, Double> averSalary) throws IOException {
BufferedReader br = new BufferedReader(new FileReader(new File(file)));
Set<Long> jobids = new HashSet<Long>();
String s = null;
while ((s = br.readLine()) != null) {
String[] cols = s.split(",");
double salary = Double.valueOf(cols[2]);
if (salary < averSalary.get(uid)) {
jobids.add(Long.parseLong(cols[0]));
}
}
br.close();
return jobids;
}

// 获取每个用户的基准比较工资：aver(浏览过的工资)*0.8
public static Map<Long, Double> getAverSalary(String file, DataModel dataModel)
throws NumberFormatException, IOException, TasteException{
Map<Long, Double> salaries = new HashMap<Long, Double>();
BufferedReader br = new BufferedReader(new FileReader(new File(file)));
String s = null;
while ((s = br.readLine()) != null) {
String[] cols = s.split(",");
salaries.put(Long.parseLong(cols[0]), Double.valueOf(cols[2]));
}
br.close();

Map<Long, Double> averSalaries = new HashMap<Long, Double>();
LongPrimitiveIterator iter = dataModel.getUserIDs();
while (iter.hasNext()) {
long uid = iter.nextLong();
FastIDSet items = dataModel.getItemIDsFromUser(uid);
LongPrimitiveIterator itemsIter = items.iterator();
double sum = 0;
int count = 0;
double aver = 0.0;
while (itemsIter.hasNext()) {
long item = itemsIter.nextLong();
double salary = salaries.get(item);
sum += salary;
count ++;
}
if(count > 0) aver = 0.8*sum/count;
averSalaries.put(uid, aver);
}
return averSalaries;
}

}