A Rule-Based Recommender System for Online Discussion Forums

Authors:
Fabian Abel;Ig Ibert Bittencourt;Nicola Henze;Daniel Krause;Julita Vassileva
Affiliations:
IVS - Semantic Web Group, Leibniz University of Hannover, Hannover, Germany D-30167;Computer Science Institute, Federal University of Alagoas, Maceio, Brazil;IVS - Semantic Web Group, Leibniz University of Hannover, Hannover, Germany D-30167;IVS - Semantic Web Group, Leibniz University of Hannover, Hannover, Germany D-30167;Department of Computer Science, University of Saskatechwan, Saskatoon, Canada SK S7N 5C9
Venue:
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Year:
2008

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Abstract

In this paper we present a rule-based personalization framework for encapsulating and combining personalization algorithms known from adaptive hypermedia and recommender systems. We show how this personalization framework can be integrated into existing systems by example of the educational online board Comtella-D, which exploits the framework for recommending relevant discussions to the users. In our evaluations we compare different recommender strategies, investigate usage behavior over time, and show that a small amount of user data is sufficient to generate precise recommendations.