Hi guys,
I'm new with mahout. I'm using it for an experimentation with
recommender system.
I'm using this code:
import org.apache.mahout.cf.taste.impl.neighborhood.*;
import org.apache.mahout.cf.taste.impl.recommender.*;
import org.apache.mahout.cf.taste.impl.similarity.*;
import org.apache.mahout.cf.taste.model.*;
import org.apache.mahout.cf.taste.neighborhood.*;
import org.apache.mahout.cf.taste.recommender.*;
import org.apache.mahout.cf.taste.similarity.*;
import java.io.*;
import java.util.*;
import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
class Example5_GroupLensRecommender {
private Example5_GroupLensRecommender() {
}
public static void main(String[] args) throws Exception {
// Istanzia il DataModel e crea alcune statistiche
DataModel model = new FileDataModel(new
File("/Users/giuseppe/NetBeansProjects/MyFirsRS/src/Mrating.csv"));
System.out.println("\nItems:"+model.getNumItems());
System.out.println("Users:"+model.getNumUsers());
// Preferences for User 1
//PreferenceArray p = model.getPreferencesFromUser(1);
// System.out.println("\nPreferences for User 1 ("+p.length()+")");
//for(int i=0; i<p.length(); i++) {
// System.out.println(p.getItemID(i)+"\t"+p.getValue(i));
//}
// Definisce i meccanismi di calcolo della similarita
//UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
UserSimilarity similarity = new SpearmanCorrelationSimilarity(model);
//UserSimilarity similarity = new EuclideanDistanceSimilarity(model);
System.out.println("\nSimilarity between User 1 and 250'");
System.out.println(similarity.userSimilarity(1, 2));
System.out.println("\nSimilarity between User 1 and 500");
System.out.println(similarity.userSimilarity(55, 50));
// Calcolo dei Neighbors
UserNeighborhood neighborhood =
new NearestNUserNeighborhood(3, similarity, model);
//new ThresholdUserNeighborhood(0.2, similarity, model);
// Mostra i neighbor
System.out.println("\nNeighbors for User 1");
long[] neighbors = neighborhood.getUserNeighborhood(1);
for(int i=0; i<neighbors.length; i++) {
System.out.println("User "+neighbors[i]+"\tsim:
"+similarity.userSimilarity(1, neighbors[i]));
}
// Istanzia il motore di raccomandazione
Recommender recommender = new GenericUserBasedRecommender(
model, neighborhood, similarity);
// Stima del Ratings
System.out.println("\nPreference Estimation for Item 103 and User1: "
+recommender.estimatePreference(1, 103));
// Calcolo delle Raccomandazioni
List<RecommendedItem> recommendations =
recommender.recommend(1, 10);
// Top-1 Recommendation
System.out.println("\nTop-1 recommendation:
"+recommendations.get(0).getItemID()+"\t"
+"Score: "+recommendations.get(0).getValue());
// Stampa tutte le raccomandazioni
for (RecommendedItem recommendation : recommendations) {
System.out.println("\n"+recommendation);
}
}
}
If I run this file (I'm using Mahout under Netbeans) I receive this error:
Similarity between User 1 and 250'
Exception in thread "main"
org.apache.mahout.cf.taste.common.NoSuchUserException: 1
at
org.apache.mahout.cf.taste.impl.model.GenericDataModel.getPreferencesFromUser(GenericDataModel.java:213)
at
org.apache.mahout.cf.taste.impl.model.file.FileDataModel.getPreferencesFromUser(FileDataModel.java:642)
at
org.apache.mahout.cf.taste.impl.similarity.SpearmanCorrelationSimilarity.userSimilarity(SpearmanCorrelationSimilarity.java:49)
at
it.uniba.dib.swap.recsys.mahout.Example5_GroupLensRecommender.main(Example5_GroupLensRecommender.java:39)
Java Result: 1
Can someone help me to understand what is the problem?
Thanks.
Dott. Giuseppe Ricci
Dottorando in Informatica XXVI ciclo
Dipartimento di Informatica
4° piano Stanza Lab. SWAP
Telefono: +39-080-5442298
E-mail: [email protected]
