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Using Bayesian Decision for Ontology Mapping

20 Pages Posted: 11 Jul 2018 First Look: Accepted

See all articles by Jie Tang

Jie Tang

Tsinghua University - Department of Computer Science and Technology

Juanzi Li

Tsinghua University - Department of Computer Science and Technology

Bangyong Liang

Tsinghua University - Department of Computer Science and Technology

Xiaotong Huang

Tsinghua University - Department of Computer Science and Technology

Yi Li

Tsinghua University - Department of Computer Science and Technology

Kehong Wang

Tsinghua University - Department of Computer Science and Technology

Abstract

Ontology mapping is the key point to reach interoperability over ontologies. In semantic web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them before processing across them. Many efforts have been conducted to automate the discovery of ontology mapping. However, some problems are still evident. In this paper, ontology mapping is formalized as a problem of decision making. In this way, discovery of optimal mapping is cast as finding the decision with minimal risk. An approach called Risk Minimization based Ontology Mapping (RiMOM) is proposed, which automates the process of discoveries on 1:1, n:1, 1:null and null:1 mappings. Based on the techniques of normalization and NLP, the problem of instance heterogeneity in ontology mapping is resolved to a certain extent. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.

Keywords: Ontology Mapping, Semantic Web, Bayesian Decision, Ontology Interoperability

Suggested Citation

Tang, Jie and Li, Juanzi and Liang, Bangyong and Huang, Xiaotong and Li, Yi and Wang, Kehong, Using Bayesian Decision for Ontology Mapping (December 2006). Journal of Web Semantics First Look. Available at SSRN: https://ssrn.com/abstract=3199344 or http://dx.doi.org/10.2139/ssrn.3199344

Jie Tang (Contact Author)

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

Juanzi Li

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

Bangyong Liang

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

Xiaotong Huang

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

Yi Li

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

Kehong Wang

Tsinghua University - Department of Computer Science and Technology ( email )

Beijing, 100084
China

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