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Shiva: A Framework for Graph based Ontology Matching

by Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 11
Year of Publication: 2014
Authors: Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar
10.5120/15678-4435

Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar . Shiva: A Framework for Graph based Ontology Matching. International Journal of Computer Applications. 89, 11 ( March 2014), 30-34. DOI=10.5120/15678-4435

@article{ 10.5120/15678-4435,
author = { Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar },
title = { Shiva: A Framework for Graph based Ontology Matching },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 11 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 30-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number11/15678-4435/ },
doi = { 10.5120/15678-4435 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:09:52.782352+05:30
%A Iti Mathur
%A Nisheeth Joshi
%A Hemant Darbari
%A Ajai Kumar
%T Shiva: A Framework for Graph based Ontology Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 11
%P 30-34
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Since long, corporations are looking for knowledge sources which can provide structured description of data and can focus on meaning and shared understanding. Structures which can facilitate open world assumptions and can be flexible enough to incorporate and recognize more than one name for an entity. A source whose major purpose is to facilitate human communication and interoperability. Clearly, databases fail to provide these features and ontologies have emerged as an alternative choice, but corporations working on same domain tend to make different ontologies. The problem occurs when they want to share their data/knowledge. Thus we need tools to merge ontologies into one. This task is termed as ontology matching. This is an emerging area and still we have to go a long way in having an ideal matcher which can produce good results. In this paper we have shown a framework to matching ontologies using graphs.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ontology Matching Ontology Alignment Graph Matching Kuhn-Munkres Algorithm.

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