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. © Springer-Verlag Berlin Heidelberg 2008.
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CITATION STYLE
Abel, F., Bittencourt, I. I., Henze, N., Krause, D., & Vassileva, J. (2008). A rule-based recommender system for online discussion forums. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5149 LNCS, pp. 12–21). https://doi.org/10.1007/978-3-540-70987-9_4
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