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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/1594

Title: Hybrid Personalization for Recommendations
Authors: Herder, Eelco
Kärger, Philipp
Keywords: personalization
recommendation
Issue Date: 25-Nov-2008
Abstract: In this paper we present the concept of hybrid personalization, the combination of multiple atomic personalization mechanisms. The idea of hybrid personalization is related to hybrid recommender systems, but works on a conceptual level—it is decoupled from the actual adaptation in the user interface. This has as an advantage that one can optimize the adaptation ‘behind the screens’ or—conversely—attach a new visualization mechanism to the personalization technique. We show the practical benefits of this layered, hybrid adaptation mechanisms by means of a case study on personalized curriculum planning where it is recommended which course could or should be followed at which state in the learning process.
Description: Herder, E., & Kärger, P. (2008). Hybrid Personalization for Recommendations. In J. Baumeister & M. Atzmüller, Proceedings of the 16th Workshop on Adaptivity and User Modeling in Interactive System, ABIS 2008 (pp. 20-25). October, 6-10, 2008, Würzburg, Germany: Universität Würzburg. Website with link to proceedings: http://lwa08.informatik.uni-wuerzburg.de/Wiki.jsp?page=FGABIS08
URI: http://hdl.handle.net/1820/1594
Appears in Collections:1. TENC: Publications and Preprints

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