Effective Data Integration in the Presence of Temporal Semantic Conflicts

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7400

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DC Field	Value	Language
dc.creator	Zhu, Hongwei	-
dc.creator	Madnick, Stuart	-
dc.creator	Siegel, Michael	-
dc.date	2004-12-10T19:16:03Z	-
dc.date	2004-12-10T19:16:03Z	-
dc.date	2004-12-10T19:16:03Z	-
dc.date.accessioned	2013-10-09T02:39:48Z	-
dc.date.available	2013-10-09T02:39:48Z	-
dc.date.issued	2013-10-09	-
dc.identifier	http://hdl.handle.net/1721.1/7400	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	The change in meaning of data over time poses significant challenges for the use of that data. These challenges exist in the use of an individual data source and are further compounded with the integration of multiple sources. In this paper, we identify three types of temporal semantic heterogeneities, which have not been addressed by existing research. We propose a solution that is based on extensions to the Context Interchange framework. This approach provides mechanisms for capturing semantics using ontology and temporal context. It also provides a mediation service that automatically resolves semantic conflicts. We show the feasibility of this approach by demonstrating a prototype that implements a subset of the proposed extensio	-
dc.format	290777 bytes	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	MIT Sloan School of Management Working Paper;4480-04	-
dc.subject	Context Interchange framework	-
dc.subject	ontology and temporal context	-
dc.title	Effective Data Integration in the Presence of Temporal Semantic Conflicts	-
dc.type	Working Paper	-
Appears in Collections:	MIT Items

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