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An adapted alternation approach for recommender systems

Abstract:

This paper presents an adaptation of the Alternation technique to tackle the pbkp_rediction task in recommender systems. These systems are widely considered in Electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted Alternation technique uses all the information stored in the system to find the pbkp_redictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted Alternation approach. © 2008 IEEE.