Inexact Matching of Ontology Graphs Using Expectation-Maximization

We present a new method for mapping ontology schemas that address similar domains. The problem of ontology mapping is crucial since we are witnessing a decentralized development and publication of ontological data. We formulate the problem of inferring a match between two ontologies as a maximum likelihood problem, and solve it using the technique of expectation-maximization (EM). Specifically, we adopt directed graphs as our model for ontologies and use a generalized version of EM to arrive at a mapping between the nodes of the graphs. We exploit the structural and lexical similarity between the graphs, and improve on previous approaches by generating a many-one correspondence between the concept nodes. We provide preliminary experimental results in support of our method and outline its limitations.

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Prashant Doshi, Christopher Thomas
• Keywords: AAAI 2006, Intelligent Agents, Maximum Likelihood Problem, Ontology Mapping, Ontology Schemas