What Happened to Content-Based Information Filtering?

  • Nikolaos Nanas
  • Anne De Roeck
  • Manolis Vavalis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5766)


Personalisation can have a significant impact on the way information is disseminated on the web today. Information Filtering can be a significant ingredient towards a personalised web. Collaborative Filtering is already being applied successfully for generating personalised recommendations of music tracks, books, movies and more. The same is not true for Content-Based Filtering. In this paper, we identify some possible reasons for the notable absence of a broad range of personalised information delivery and dissemination services on the web today. We advocate that a more holistic approach to user profiling is required and we discuss the series of still open, challenging research issues raised.


Recommender System Collaborative Filter Information Item User Interest Personalise Recommendation 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Nikolaos Nanas
    • 1
  • Anne De Roeck
    • 2
  • Manolis Vavalis
    • 1
  1. 1.Laboratory for Information Systems and ServicesCentre for Research and Technology - Thessaly (CERETETH)Greece
  2. 2.Computing DepartmentThe Open UniversityUK

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