A probabilistic approach for modelling user preferences in recommender systems: a case study on IBM watson analytics

Parisa Lak, Can Kavaklioglu, Mefta Sadat, Martin Petitclerc, Graham Wills, Andriy V. Miranskyy, Ayse Basar Bener. A probabilistic approach for modelling user preferences in recommender systems: a case study on IBM watson analytics. In Marcellus Mindel, Kelly Lyons, Joe Wigglesworth, editors, Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering, CASCON 2017, Markham, Ontario, Canada, November 6-8, 2017. pages 38-47, IBM / ACM, 2017. [doi]

Abstract

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