Abstract
User modelling and personalisation are the key aspects of recommender systems in terms of recommendation quality. While being very efficient and designed to work with huge amounts of data, present recommender systems often lack the facility of user integration when it comes to feedback and direct user modelling. In this paper we describe ERASP, 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, with the purpose of enhancing recommendations. We present promising experimental results.
Partially supported by FCT Scholarship SFRH/BD/38214/2007.
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Ilic, M., Leite, J., Slota, M. (2008). Explicit Dynamic User Profiles for a Collaborative Filtering Recommender System. In: Geffner, H., Prada, R., Machado Alexandre, I., David, N. (eds) Advances in Artificial Intelligence – IBERAMIA 2008. IBERAMIA 2008. Lecture Notes in Computer Science(), vol 5290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88309-8_36
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DOI: https://doi.org/10.1007/978-3-540-88309-8_36
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