Proceedings of the 2007 Industrial Engineering Research Conference

A Probabilistic Framework for Semantic Similarity and Ontology Mapping

Yun Peng, Zhongli Ding, Rong Pan, Yang Yu, Boonserm (Serm) Kulvatunyou, Nenad Ivezik, Albert Jones, and Hyunbo Cho

May 19, 2007

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.

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Type: InProceedings

Publisher: Institute of Industrial Engineers

Downloads: 2380 downloads