Personalized information retrieval based on context and ontological knowledge

Mylonas, Ph; Vallet, D; Castells, P; Fernandez, M; Avrithis, Y

dc.contributor.author	Mylonas, Ph	en
dc.contributor.author	Vallet, D	en
dc.contributor.author	Castells, P	en
dc.contributor.author	Fernandez, M	en
dc.contributor.author	Avrithis, Y	en
dc.date.accessioned	2014-03-01T01:28:59Z
dc.date.available	2014-03-01T01:28:59Z
dc.date.issued	2008	en
dc.identifier.issn	0269-8889	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19067
dc.subject	Context Model	en
dc.subject	Information Retrieval	en
dc.subject	User Preferences	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	Computer simulation	en
dc.subject.other	Fuzzy logic	en
dc.subject.other	Knowledge management	en
dc.subject.other	Reliability	en
dc.subject.other	Semantics	en
dc.subject.other	Automatic interpretation	en
dc.subject.other	Context modeling	en
dc.subject.other	Contextualization	en
dc.subject.other	Fuzzy representations	en
dc.subject.other	Information retrieval	en
dc.title	Personalized information retrieval based on context and ontological knowledge	en
heal.type	journalArticle	en
heal.identifier.primary	10.1017/S0269888907001282	en
heal.identifier.secondary	http://dx.doi.org/10.1017/S0269888907001282	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Context modeling has long been acknowledged as a key aspect in a wide variety of problem domains. In this paper we focus on the combination of contextualization and personalization methods to improve the performance of personalized information retrieval. The key aspects in our proposed approach are (1) the explicit distinction between historic user context and live user context, (2) the use of ontology-driven representations of the domain of discourse, as a common, enriched representational ground for content meaning, user interests, and contextual conditions, enabling the definition of effective means to relate the three of them, and (3) the introduction of fuzzy representations as an instrument to properly handle the uncertainty and imprecision involved in the automatic interpretation of meanings, user attention, and user wishes. Based on a formal grounding at the representational level, we propose methods for the automatic extraction of persistent semantic user preferences, and live, ad-hoc user interests, which are combined in order to improve the accuracy and reliability of personalization for retrieval. © 2008 Cambridge University Press.	en
heal.publisher	CAMBRIDGE UNIV PRESS	en
heal.journalName	Knowledge Engineering Review	en
dc.identifier.doi	10.1017/S0269888907001282	en
dc.identifier.isi	ISI:000255250500005	en
dc.identifier.volume	23	en
dc.identifier.issue	1	en
dc.identifier.spage	73	en
dc.identifier.epage	100	en