Abstract
Recommendation systems have received significant attention, with most of the proposed methods focusing on recommendations for single users. Recently, there are also approaches aiming at either group or context-aware recommendations. In this paper, we address the problem of contextual recommendations for groups. We exploit a hierarchical context model to extend a typical recommendation model to a general context-aware one that tackles the information needs of a group. We base the computation of contextual group recommendations on a subset of preferences of the users that present the most similar behavior to the group, that is, the users with the most similar preferences to the preferences of the group members, for a specific context. This subset of preferences includes the ones with context equal to or more general than the given context.
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Stefanidis, K., Shabib, N., Nørvåg, K., Krogstie, J. (2012). Contextual Recommendations for Groups. In: Castano, S., Vassiliadis, P., Lakshmanan, L.V., Lee, M.L. (eds) Advances in Conceptual Modeling. ER 2012. Lecture Notes in Computer Science, vol 7518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33999-8_11
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DOI: https://doi.org/10.1007/978-3-642-33999-8_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33998-1
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