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

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.

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