Designing the context matching engine for evaluating and selecting context information sources

Chantzara, M; Anagnostou, M

dc.contributor.author	Chantzara, M	en
dc.contributor.author	Anagnostou, M	en
dc.date.accessioned	2014-03-01T01:22:09Z
dc.date.available	2014-03-01T01:22:09Z
dc.date.issued	2005	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16468
dc.subject	Context Information	en
dc.subject	context-aware service	en
dc.subject	Difference Set	en
dc.subject	User Preferences	en
dc.subject	User Satisfaction	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	MANAGEMENT	en
dc.subject.other	SERVICES	en
dc.title	Designing the context matching engine for evaluating and selecting context information sources	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/11740674_7	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11740674_7	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	The easy creation of context-aware services requires the support of management facilities that provide ways to more easily acquire, represent and distribute context information. This paper claims that the quality level of a context-aware service determines the context information to be obtained. On the other hand, using context data produced by unsteady sources may affect the users' satisfaction. In this perspective, we introduce the Context Matching Engine that trades off the cost, the user preferences and the quality of the available context information in order to discover the best context sources for each customized context-aware service. According to the proposed approach, there is no need for the services to know beforehand the context providers to retrieve information, but the evaluation and the quality-aware selection of the context information on context request are envisioned. Finally, it allows services to be ported easily to environments with different set of context sources.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	MODELING AND RETRIEVAL OF CONTEXT	en
heal.bookName	LECTURE NOTES IN ARTIFICIAL INTELLIGENCE	en
dc.identifier.doi	10.1007/11740674_7	en
dc.identifier.isi	ISI:000238187500007	en
dc.identifier.volume	3946	en
dc.identifier.spage	101	en
dc.identifier.epage	117	en