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A Rule-Based Recommender System for Online Discussion Forums

  • Fabian Abel
  • Ig Ibert Bittencourt
  • Nicola Henze
  • Daniel Krause
  • Julita Vassileva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5149)

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.

Keywords

Recommender System Discussion Forum User Feedback Implicit Feedback Explicit Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Abel, F., Baumgartner, R., Brooks, A., Enzi, C., Gottlob, G., Henze, N., Herzog, M., Kriesell, M., Nejdl, W., Tomaschewski, K.: The personal publication reader, semantic web challenge 2005. In: 4th International Semantic Web Conference (November 2005)Google Scholar
  2. 2.
    Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)CrossRefGoogle Scholar
  3. 3.
    Brusilovsky, P.: Adaptive Hypermedia. User Modeling and User-Adapted Interaction 11, 87–110 (2001)MATHCrossRefGoogle Scholar
  4. 4.
    Webster, A., Vassileva, J.: Visualizing personal relations in online communities. In: Wade, V.P., Ashman, H., Smyth, B. (eds.) AH 2006. LNCS, vol. 4018, pp. 223–233. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  5. 5.
    Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating “word of mouth”. In: Proceedings of ACM CHI 1995 Conference on Human Factors in Computing Systems, vol. 1, pp. 210–217 (1995)Google Scholar
  6. 6.
    Burke, R.: Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002)MATHCrossRefGoogle Scholar
  7. 7.
    Brusilovsky, P., Henze, N.: Open corpus adaptive educational hypermedia. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 671–696. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Fabian Abel
    • 2
  • Ig Ibert Bittencourt
    • 1
  • Nicola Henze
    • 2
  • Daniel Krause
    • 2
  • Julita Vassileva
    • 3
  1. 1.Computer Science InstituteFederal University of AlagoasMaceioBrazil
  2. 2.IVS - Semantic Web GroupLeibniz University of HannoverHannoverGermany
  3. 3.Department of Computer ScienceUniversity of SaskatechwanSaskatoonCanada

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