Temporal collaborative filtering with adaptive neighbourhoods

ABSTRACT

Collaborative Filtering aims to predict user tastes, by minimising the mean error produced when predicting hidden user ratings. The aim of a deployed recommender system is to iteratively predict users' preferences over a dynamic, growing dataset, and system administrators are confronted with the problem of having to continuously tune the parameters calibrating their CF algorithm. In this work, we formalise CF as a time-dependent, iterative prediction problem. We then perform a temporal analysis of the Netflix dataset, and evaluate the temporal performance of two CF algorithms. We show that, due to the dynamic nature of the data, certain prediction methods that improve prediction accuracy on the Netflix probe set do not show similar improvements over a set of iterative train-test experiments with growing data. We then address the problem of parameter selection and update, and propose a method to automatically assign and update per-user neighbourhood sizes that (on the temporal scale) outperforms setting global parameters.

REFERENCES

• 1: Jonathan L. Herlocker , Joseph A. Konstan , Loren G. Terveen , John T. Riedl, Evaluating collaborative filtering recommender systems, ACM Transactions on Information Systems (TOIS), v.22 n.1, p.5-53, January 2004 [doi>10.1145/963770.963772]
• 2: G. Potter. Putting the Collaborator Back Into Collaborative Filtering. In Proceedings of the 2nd Netflix-KDD Workshop, 2008.
• 3: Robert M. Bell , Yehuda Koren, Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights, Proceedings of the 2007 Seventh IEEE International Conference on Data Mining, p.43-52, October 28-31, 2007 [doi>10.1109/ICDM.2007.90]
• 4: N. Lathia, S. Hailes, and L. Capra. Temporal Collaborative Filtering With Adaptive Neighbourhoods (Extended Version). In Research Note RN/09/03, Dept. of Computer Science, University College London, London, UK, April 2009.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

General Terms:
Algorithms

Keywords:
temporal collaborative filtering