Personalized content retrieval in context using ontological knowledge
Metadatos
Title:
Personalized content retrieval in context using ontological knowledge
Author:
Vallet Weadon, David Jordi; Castells, Pablo; Fernández Sánchez, Miriam; Mylonas, Phivos; Avrithis, Yannis
Entity:
UAM. Departamento de Ingeniería Informática
UAM Author:
Castells Azpilicueta, Pablo
; Fernández Sánchez, Miriam
; Vallet Weadon, David Jordi
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Date:
2007-03
Citation:
10.1109/TCSVT.2007.890633
IEEE Transactions on Circuits and Systems for Video Technology 17.3 (2007): 336-346
ISSN:
1051-8215 (print); 1558-2205 (online)
DOI:
10.1109/TCSVT.2007.890633
Funded by:
This research was supported by the European Commission (FP6-001765 – aceMedia), and the Spanish Ministry of Science and Education (TIN2005-06885)
Project:
info:eu-repo/grantAgreement/EC/FP6/001765
Editor's Version:
http://dx.doi.org/10.1109/TCSVT.2007.890633
Subjects:
Content search and retrieval; Context modeling; Ontology; Personalization; Informática
Note:
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Vallet, D., Castells, P., Fernandez, M., Mylonas, P., Avrithis, Y. "Personalized Content Retrieval in Context Using Ontological Knowledge". IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 3, pp. 336-346, March 2007
Rights:
© 2007 IEEE
Abstract:
Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context.
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