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

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3 Author(s)
Manoela Ilic ; Univ. Nova de Lisboa, Lisbon ; João Leite ; Martin Slota

User modeling and personalization 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.

Published in:

Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on  (Volume:1 )

Date of Conference:

9-12 Dec. 2008