A Probabilistic Framework for Semantic Similarity and Ontology Mapping
| dc.contributor.author | Peng, Yun | |
| dc.contributor.author | Ding, Zhongli | |
| dc.contributor.author | Pan, Rong | |
| dc.contributor.author | Yu, Yang | |
| dc.contributor.author | Kulvatunyou, Boonserm | |
| dc.contributor.author | Ivezik, Nenad | |
| dc.contributor.author | Jones, Albert | |
| dc.contributor.author | Cho, Hyunbo | |
| dc.date.accessioned | 2018-11-29T18:29:55Z | |
| dc.date.available | 2018-11-29T18:29:55Z | |
| dc.date.issued | 2007-05-19 | |
| dc.description | Proceedings of the 2007 Industrial Engineering Research Conference | en_US |
| dc.description.abstract | We propose a probabilistic framework to address uncertainty in ontology-based semantic integration and interopera- tion. This framework consists of three main components: 1) BayesOWL that translates an OWL ontology to a Bayesian network, 2) SLBN (Semantically Linked Bayesian Networks) that support reasoning across translated BNs, and 3) a Learner that learns from the web the probabilities needed by the other modules. This framework expands the semantic web and can serve as a theoretical basis for solving real world semantic integration problems. | en_US |
| dc.description.sponsorship | This work was supported in part by NSF award IIS-0326460 and NIST award 60NANB6D6206. | en_US |
| dc.description.uri | https://ebiquity.umbc.edu/paper/html/id/389/A-Probabilistic-Framework-for-Semantic-Similarity-and-Ontology-Mapping | en_US |
| dc.format.extent | 6 pages | en_US |
| dc.genre | conference papers and proceedings preprints | en_US |
| dc.identifier | doi:10.13016/M2GH9BD60 | |
| dc.identifier.uri | http://hdl.handle.net/11603/12129 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Institute of Industrial Engineers | 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 work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law | |
| dc.rights | Public Domain Mark 1.0 | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/mark/1.0/ | * |
| dc.subject | Semantic web | en_US |
| dc.subject | uncertainty | en_US |
| dc.subject | integration | en_US |
| dc.subject | ontology | en_US |
| dc.subject | Bayesian networks | en_US |
| dc.subject | UMBC Ebiquity Research Group | en_US |
| dc.title | A Probabilistic Framework for Semantic Similarity and Ontology Mapping | en_US |
| dc.type | Text | en_US |