Scalable Dynamic User Preferences for Recommender Systems through the Use of the Well-Founded Semantics

Authors:
Manoela Ilic;João Leite;Martin Slota
Affiliations:
-;-;-
Venue:
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Year:
2008

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Abstract

User modeling and personalisation are the key aspects of recommender systems in terms of recommendation quality. ERASP is an add-on to existing recommender systems which uses dynamic logic programming -- an extension of answer set programming -- as a means for users to specify and update their models and preferences, with the purpose of enhancing recommendations. While being an excellent solution in recommender systems limited to a few thousand products, ERASP does not scale well beyond that point. In this paper we present a major theoretical redesign of ERASP which entails a significant improvement in the performance of its implementation, making it usable in domains with hundreds of thousands of products.