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Intelligent media indexing and television recommender systems

Third BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2009) (FDIA)

Computers XXIII Celebrating People and Technology

1 September 2009

Collaborative filtering, recommender system, multimedia retrieval, personalised television

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      Abstract

      This paper presents a state-of-art review on recommender systems that has been identified as possible areas of my research. It describes the current generation of collaborative filtering methods which are usually classified into three main categories: item-based, user-based and hybrid methods. The paper considers these methods to be applied to digital television providing recommendation for viewers. Personalised television is predicted to be the next step in the evolution of television which might reshape the whole landscape of mass media. The paper also identifies anticipated problems in the domain of recommender systems which includes indexing, collaborative filtering, ranking problems and possible research directions to solve these problems. Finally, these challenges are considered in the domain of personalised television which has its own inherent shortcomings.

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      Author and article information

      Affiliations
      Department of Computer Science

      University College London
      Contributors
      Conference
      September 2009
      September 2009
      : 50-55
      10.14236/ewic/FDIA2009.9
      © Tamas Jambor. Published by BCS Learning and Development Ltd. Third BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2009), Padua, Italy

      This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

      Third BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2009)
      FDIA
      3
      Padua, Italy
      1 September 2009
      Electronic Workshops in Computing (eWiC)
      Computers XXIII Celebrating People and Technology
      Product
      Product Information: 1477-9358 BCS Learning & Development
      Self URI (journal page): https://ewic.bcs.org/
      Categories
      Electronic Workshops in Computing

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