An Black-Box Testing Approach on User Modeling in Practical Movie Recommendation Systems

  • Xuan Hau Pham
  • Tu Ngoc Luong
  • Jason J. Jung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8083)

Abstract

Since there have been many practical recommendation services in real world, main research questions are i) how such services provide users with recommendations, and ii) how they are different from each other. The aim of this paper is to evaluate user modeling process in several practical recommendation systems. Black-box testing scheme has been applied by comparing recommendation results. User models (i.e., a set of user ratings) have been synthesized to discriminate the recommendation results. Particularly, we focus on investigating whether the services consider attribute selection.

Keywords

Recommendation systems Personalization User modeling Black-box testing Comparative study 

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References

  1. 1.
    Pu, P., Chen, L., Hu, R.: Evaluating recommender systems from the user’s perspective: survey of the state of the art. User Modeling and User-Adapted Interaction 22(4-5), 317–355 (2012)CrossRefGoogle Scholar
  2. 2.
    Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1), 5–53 (2004)CrossRefGoogle Scholar
  3. 3.
    Jung, J.J.: Attribute selection-based recommendation framework for short-head user group: An empirical study by movielens and imdb. Expert Systems with Applications 39(4), 4049–4054 (2012)CrossRefGoogle Scholar
  4. 4.
    Beizer, B.: Black-Box Testing: Techniques for Functional Testing of Software and Systems. John Wiley & Sons (1995)Google Scholar
  5. 5.
    Reisinger, D.: Top 10 movie recommendation engines (March 2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xuan Hau Pham
    • 1
  • Tu Ngoc Luong
    • 1
  • Jason J. Jung
    • 1
  1. 1.Knowledge Engineering Laboratory, Department of Computer EngineeringYeungnam UniversityKorea

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