Ontology Matching Techniques: A Gold Standard Model
Alok Chauhan1, Vijayakumar V2, Layth Sliman3

1Alok Chauhan, School of Computing Science & Engineering, Visvesvaraya Technological University, Chennai (TamilNadu), India.

2Vijayakumar V, School of Computing Science & Engineering, University, Chennai (TamilNadu), India.

3Layth Sliman, School of Computing Science & Engineering, University, Chennai (TamilNadu), India.

Manuscript received on 04 April 2019 | Revised Manuscript received on 11 April 2019 | Manuscript Published on 26 April 2019 | PP: 370-373 | Volume-8 Issue-6S April 2019 | Retrieval Number: F61330486S19/19©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Typically an ontology matching technique is a combination of much different type of matchers operating at various abstraction levels such as structure, semantic, syntax, instance etc. An ontology matching technique which employs matchers at all possible abstraction levels is expected to give, in general, best results in terms of precision, recall and F-measure due to improvement in matching opportunities and if we discount efficiency issues which may improve with better computing resources such as parallel processing. A gold standard ontology matching model is derived from a model classification of ontology matching techniques. A suitable metric is also defined based on gold standard ontology matching model. A review of various ontology matching techniques specified in recent research papers in the area was undertaken to categorize an ontology matching technique as per newly proposed gold standard model and a metric value for the whole group was computed. The results of the above study support proposed gold standard ontology matching model.

Keywords: Ontology Matching, Gold Standard, Metric etc.
Scope of the Article: Parallel Computing