Recommender system: simple user-based collaborative filtering to evaluate with precision and recall

java recommendation-engine collaborative-filtering precision-recall
Thomas picture Thomas · May 12, 2011 · Viewed 7k times · Source

I'm looking for a very simple implementation in Java of a user-based collaborative filtering. I would like to evaluate the precision and recall of this CF with the movielens dataset. I've seen that the performance (F1) should be around 20 to 30% (with Pearson similarity, and KNN).

Does this simple framework exist with the evaluation for precision and recall code?

Answer

Sean Owen picture Sean Owen · May 19, 2011

Apache Mahout does everything you mention here. It is Java-based, and supports user-based collaborative filtering (among others) with GenericUserBasedRecommender. It is a k-nearest-neighbor algorithm, into which you can plug similarity implementations like PearsonCorrelationSimilarity and others.

Look at the org.apache.mahout.cf.taste package and subpackages. In the .impl.eval subpackage find GenericRecommenderIRStatsEvaluator. This will run a test that reports precision, recall and F1.

Finally, there are already some working examples based on GroupLens in mahout-examples.

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