A novel ontology matching approach using key concepts

Pages99-111
DOIhttps://doi.org/10.1108/AJIM-04-2015-0054
Date18 January 2016
Published date18 January 2016
AuthorTayybah Kiren,Muhammad Shoaib
Subject MatterLibrary & information science,Information behaviour & retrieval
A novel ontology matching
approach using key concepts
Tayybah Kiren and Muhammad Shoaib
University of Engineering and Technology, Lahore, Pakistan
Abstract
Purpose Ontologies are used to formally describe the concepts within a domain in a machine-
understandable way. Matching of heterogeneous ontologies is often essential for many applications
like semantic annotation, query answering or ontology integration. Some ontologies may include a
large number of entities which make the ontology matching process very complex in terms of the
search space and execution time requirements. The purpose of this paper is to present a technique for
finding degree of similarity between ontologies that trims down the search space by eliminating
the ontology concepts that have less likelihood of being matched.
Design/methodology/approach Algorithmsare written for finding keyconcepts, concept matching
and relationshipmatching. WordNet is used forsolving synonym problems during the matchingprocess.
The technique is evaluated using the reference alignments betweenontologies from ontology alignment
evaluation initiative benchmark in termsof degree of similarity, Pearsons correlation coefficientand IR
measures precision, recall and F-measure.
Findings Positive correlation between the degree of similarity and degree of similarity (reference
alignment) and computed values of precision, recall and F-measure showed that if only key concepts of
ontologies are compared, a time and search space efficient ontology matching system can
be developed.
Originality/value On the basis of the present novel approach for ontology matching, it is concluded
that using key concepts for ontology matching gives comparable results in reduced time and space.
Keywords Ontology matching, Ontology, Degree of similarity, Effectiveness measures,
Key concepts, Ontology heterogeneity
Paper type Research paper
1. Introduction
The World Wide Web (WWW) is widely used as a worldwide medium for information
sharing. Interoperability among disparate information systems in the WWW is
limited because of the information heterogeneity (Mao, 2008). Ontologies are
recommended as a way to resolve this problem by expressing and exchanging the
information in a formal and explicit way. However, ontologiesthemselves suffer from
the problem of heterogeneity. Ontology developers from different domains may
interpret the same data in different ways and develop the ontologies having similar
concepts represented with different names. This leads to heterogeneity, such as
variation in naming and describing a concept in different levels of detail. This
heterogeneity hampers the interoperability among distributed information systems.
Ontology heterogeneity occurs, for instance, when one ontology only has the concept
humans, while another ontology has further male and female sub-concepts, or when
semantically similar classes in two ontologies have different instances. When terms
in two ontologies have a different syntax but the same meaning, this is also
called ontology heterogeneity. A clearer indication of the existence of ontology
heterogeneity is experienced while querying through the SWOOGLE semantic web
search engine. If we query for the concept Apple,it returns 254 results for apple.
In some of the resulting semantic web documents (RDF or owl) apple means a
computer and some results represent apple as a fruit. Also the same concept can be
Aslib Journal of Information
Management
Vol. 68 No. 1, 2016
pp. 99-111
©Emerald Group Publis hing Limited
2050-3806
DOI 10.1108/AJIM-04-2015-0054
Received 10 April 2015
Revised 28 October 2015
Accepted 2 November 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2050-3806.htm
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Novel
ontology
matching
approach

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