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Knowledge Integration to Overcome Ontological Heterogeneity: Challenges from Financial Information Systems

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dc.creator Firat, Aykut
dc.creator Madnick, Stuart E.
dc.creator Grosof, Benjamin
dc.date 2003-11-16T18:41:15Z
dc.date 2003-11-16T18:41:15Z
dc.date 2003-01
dc.date.accessioned 2013-10-09T02:31:56Z
dc.date.available 2013-10-09T02:31:56Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/3683
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description The shift towards global networking brings with it many opportunities and challenges. In this paper, we discuss key technologies in achieving global semantic interoperability among heterogeneous information systems, including both traditional and web data sources. In particular, we focus on the importance of this capability and technologies we have designed to overcome ontological heterogeneity, a common type of disparity in financial information systems. Our approach to representing and reasoning with ontological heterogeneities in data sources is an extension of the Context Interchange (COIN) framework, a mediator-based approach for achieving semantic interoperability among heterogeneous sources and receivers. We also analyze the issue of ontological heterogeneity in the context of source-selection, and offer a declarative solution that combines symbolic solvers and mixed integer programming techniques in a constraint logic-programming framework. Finally, we discuss how these techniques can be coupled with emerging Semantic Web related technologies and standards such as Web-Services, DAML+OIL, and RuleML, to offer scalable solutions for global semantic interoperability. We believe that the synergy of database integration and Semantic Web research can make significant contributions to the financial knowledge integration problem, which has implications in financial services, and many other e-business tasks.
dc.description Singapore-MIT Alliance (SMA)
dc.format 147887 bytes
dc.format application/pdf
dc.language en_US
dc.relation Computer Science (CS);
dc.subject database integration
dc.subject Semantic Web ontologies
dc.subject source selection
dc.title Knowledge Integration to Overcome Ontological Heterogeneity: Challenges from Financial Information Systems
dc.type Article


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