| Building intelligent systems in open, heterogeneous, dynamic, distributed environments | 12 May 2008, 00:34:24 EDT ![]() |
|||
A Probabilistic Framework for Semantic Similarity and Ontology Mapping Authors: Yun Peng, Zhongli Ding, Rong Pan, Yang Yu, Boonserm Kulvatunyou, Nenad Ivezik, Albert Jones, and Hyunbo Cho Book Title: Proceedings of the 2007 Industrial Engineering Research Conference Date: May 19, 2007 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 Baye- sian 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. Type: InProceedings Publisher: Institute of Industrial Engineers Google Scholar: search Number of downloads: 72 Available for download as
Bookmark at: Digg | Del.icio.us | Connotea | CiteULike |
| Home | About Us | Contact Us | Site Map | Legal | Privacy Copyright © 1999-2008 UMBC ebiquity research group. Copyright © 2003-2008 Site design and RGB engine code by Filip Perich. XG Page gen 0.025 sec. |