Measuring the degree of similarity between web ontologies based on semantic coherence

Authors:
Abhik Banerjee;Hareendra Munimadugu;Srinivasa Raghavan Vedanarayanan;Lawrence J. Mazlack
Affiliations:
Applied Computational Intelligence Laboratory, University of Cincinnati, Ohio;Applied Computational Intelligence Laboratory, University of Cincinnati, Ohio;Applied Computational Intelligence Laboratory, University of Cincinnati, Ohio;Applied Computational Intelligence Laboratory, University of Cincinnati, Ohio
Venue:
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Year:
2010

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Abstract

The Internet comprises of a variety of websites, which both individually and in clusters generate large amounts of information. In order to make web pages machine-understandable we need a formal, explicit specification. This is provided by a Web Ontology. The importance of domain ontologies is widely recognized, particularly in its relation to the expected advent of the Semantic Web. For the task of detecting and recovering relevant ontologies, a means to measure the similarity between ontologies becomes a binding necessity on a vary large scale. The purpose of this paper is to describe a method that will effectively recognize and categorize different ontologies of the same domain and find the degree similarity between them to provide a framework for a research that can effectively provide a scope for merging the ontologies that relate to a similar concept in a domain.