Affective recommender systems: The role of emotions in recommender systems
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Recommender systems have traditionally relied on data-centric descriptors for content and user modeling. In recent years we have witnessed an increasing number of attempts to use emotions in di?erent ways to improve the quality of recommender systems. In this paper we introduce a unifying framework that positions the research work, that has been done so far in a scattered manner, in a three stage model. We provide examples of research that cover various aspects of the detection of emotions and the inclusion of emotions into recommender systems.
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Proceedings of the Workshop on Location-Aware Recommendations (LocalRec 2015) co-located with the 9th ACM Conference on Recommender Systems (RecSys 2015) Bouros, P; Lathia, N; Renz, M; Ricci, F; Sacharidis, D (CEUR, 2015)
Jannach D; Zanker M; Ge M; Gröning M (Springer Berlin Heidelberg, 2012)The paper reviews and classifies recent research in recommender systems both in the field of Computer Science and Information Systems. The goal of this work is to identify existing trends, open issues and possible directions ...
Emotive and personality parameters in recommender systems: Recognition and usage of user-centric data for user and item modeling in content retrieval systems Tkalčič M; Košir A; Tasič JF (LAP LAMBERT Academic Publishing, 2011)The growing amount of multimedia content is making it hard for end users to find the relevant content. The goal of recommender systems is to assist the users by finding a small subset of relevant multimedia items for each ...