Vallet, D.; Castells, P.; Fernandez, M.; Mylonas, P. and Avrithis, Y.
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|DOI (Digital Object Identifier) Link:||http://doi.org/10.1109/TCSVT.2007.890633|
|Google Scholar:||Look up in Google Scholar|
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.
|Item Type:||Journal Article|
|Copyright Holders:||2007 IEEE|
|Extra Information:||(c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.|
|Keywords:||content search and retrieval; context modeling; ontology; personalization|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||26 Apr 2011 10:04|
|Last Modified:||05 Aug 2016 18:51|
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