A Multi-Purpose Ontology-Based Approach for Personalised Content Filtering and Retrieval

  • Iván Cantador
  • Miriam Fernández
  • David Vallet
  • Pablo Castells
  • Jérôme Picault
  • Myriam Ribière
Part of the Studies in Computational Intelligence book series (SCI, volume 93)


Personalised multimedia access aims at enhancing the retrieval process by complementing explicit user requests with implicit user preferences. We propose and discuss the benefits of the introduction of ontologies for an enhanced representation of the relevant knowledge about the user, the context, and the domain of discourse, as a means to enable improvements in the retrieval process and the performance of adaptive capabilities. We develop our proposal by describing techniques in several areas that exemplify the exploitation of the richness and power of formal and explicit semantics descriptions, and the improvements therein. In addition, we discuss how those explicit semantics can be learnt automatically from the analysis of the content consumed by a user, determining which concepts appear to be significant for the user’s interest representation. The introduction of new preferences on the user profile should correspond to heuristics that provide a trade-off between consistency and persistence of the user’s implicit interests.


User Preference Domain Ontology User Interest Decay Factor Concept History 
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 2008

Authors and Affiliations

  • Iván Cantador
    • 1
  • Miriam Fernández
    • 1
  • David Vallet
    • 1
  • Pablo Castells
    • 1
  • Jérôme Picault
    • 2
  • Myriam Ribière
    • 2
  1. 1.Escuela Politécnica SuperiorUniversidad Autónoma de MadridMadridSpain
  2. 2.Parc Les AlgorithmesMotorola LabsGif-sur-YvetteFrance

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