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Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico
(2006).
URL: http://www.cild.iastate.edu/events/aaai06symposium...
Abstract
This paper describes a framework for integrating similarity measures and Dempster-Shafer belief functions for data integration in the context of multi agent ontology mapping. In order to incorporate uncertainty inherent to the ontology mapping process, we propose utilizing the Dempster-Shafer model for dealing with incomplete and uncertain information produced during the mapping. A novel approach is presented how assessing belief can influence the similarities originally created by both syntactic and semantic similarity algorithms. Our approach is an alternative to the classical Bayesian reasoning which has been investigated for improving the efficiency of creating ontology mappings.
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- Item ORO ID
- 23621
- Item Type
- Conference or Workshop Item
- Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2006 The Authors
- Depositing User
- Kay Dave