A Bayesian Approach to Uncertainty Modeling in OWL Ontology
dc.contributor.author | Ding, Zhongli | |
dc.contributor.author | Peng, Yun | |
dc.contributor.author | Pan, Rong | |
dc.date.accessioned | 2018-12-12T19:22:27Z | |
dc.date.available | 2018-12-12T19:22:27Z | |
dc.date.issued | 2004-11-15 | |
dc.description | Proceedings of the International Conference on Advances in Intelligent Systems - Theory and Applications | en_US |
dc.description.abstract | Dealing with uncertainty is crucial in ontology engineering tasks such as domain modeling, ontology reasoning, and concept mapping between ontologies. This paper presents our on-going research on modeling uncertainty in ontologies based on Bayesian networks (BN). This includes 1) extending OWL to allow additional probabilistic markups for attaching probability information, 2) directly converting a probabilistically annotated OWL ontology into a BN structure by a set of structural translation rules, and 3) constructing the conditional probability tables (CPTs) of this BN using a new method based on iterative proportiobal fitting procedure (IPFP). The translated BN can support more accurate ontology reasoning under uncertainty as Bayesian inferences. | en_US |
dc.description.sponsorship | This work was supported in part by DARPA contract F30602-97-1-0215. | en_US |
dc.description.uri | https://ebiquity.umbc.edu/paper/html/id/204/A-Bayesian-Approach-to-Uncertainty-Modeling-in-OWL-Ontology | en_US |
dc.format.extent | 9 pages | en_US |
dc.genre | conference papers and proceedings preprints | en_US |
dc.identifier | doi:10.13016/M23J3951P | |
dc.identifier.uri | http://hdl.handle.net/11603/12236 | |
dc.language.iso | en_US | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.relation.ispartof | UMBC Student Collection | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.subject | bayesian networks | en_US |
dc.subject | ontology | en_US |
dc.subject | semantic web | en_US |
dc.subject | uncertainity | en_US |
dc.subject | UMBC Ebiquity Research Group | en_US |
dc.title | A Bayesian Approach to Uncertainty Modeling in OWL Ontology | en_US |
dc.type | Text | en_US |
Files
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 2.56 KB
- Format:
- Item-specific license agreed upon to submission
- Description: