I am learning to use mahout by starting with a example copied from the

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Asked: May 23, 20262026-05-23T04:17:37+00:00 2026-05-23T04:17:37+00:00

I am learning to use mahout by starting with a example copied from the

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I am learning to use mahout by starting with a example copied from the book. However, the eclipse compiler gives me the following message:

> Exception in thread "main" java.lang.NoClassDefFoundError: org/slf4j/LoggerFactory
    at org.apache.mahout.cf.taste.impl.model.file.FileDataModel.<clinit>(FileDataModel.java:119)
    at mia.recommender.ch02.RecommenderIntro.main(RecommenderIntro.java:18)
Caused by: java.lang.ClassNotFoundException: org.slf4j.LoggerFactory
    at java.net.URLClassLoader$1.run(URLClassLoader.java:202)
    at java.security.AccessController.doPrivileged(Native Method)
    at java.net.URLClassLoader.findClass(URLClassLoader.java:190)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:307)
    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:301)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:248)
    ... 2 more

It seems to me that the the problem comes from FileDataModel.java, which belongs to this libary itself. How to trace back or analyze this error.

The example code is given as follows, which exactly is the one copied from the book. The line causing the trouble is

DataModel model = new FileDataModel(new File("intro.csv")); 


import org.apache.mahout.cf.taste.impl.model.file.*;
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.*;
class RecommenderIntro {
  public static void main(String[] args) throws Exception {


    DataModel model = new FileDataModel(new File("intro.csv")); 
    UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
    UserNeighborhood neighborhood =
      new NearestNUserNeighborhood(2, similarity, model);
    Recommender recommender = new GenericUserBasedRecommender(
        model, neighborhood, similarity); 
    List<RecommendedItem> recommendations =
        recommender.recommend(1, 1); 
    for (RecommendedItem recommendation : recommendations) {
      System.out.println(recommendation);
    }
  }
}