Dynamic Inter-Domain Multiple Ontology Mapping

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2016 by IJETT Journal
Volume-36 Number-4
Year of Publication : 2016
Authors : Mannar Mannan. J, Sudha.T, Sundarambal. M


Mannar Mannan. J, Sudha.T, Sundarambal. M"Dynamic Inter-Domain Multiple Ontology Mapping", International Journal of Engineering Trends and Technology (IJETT), V36(4),174-179 June 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

In the present information age, data integration and reuse over online is a challenging task. This type of distributed data reuse suffers due to platform, format, structure, standard, and other things. Ontology is broadly used to represents complete knowledge about the particular domain that capable of reuse. Ontology mapping provides integrated knowledge diffuse perspective of interrelated domain. To map multiple inter-related ontologies, this paper proposed class-match mapping algorithm, where classes of ontology is semantically compared with classes of mapped ontologies. Here, the WordNet is used as background knowledge and Wu and Palmer semantic distance measurement techniques used to measure the relationship between classes. This proposed method, perform better for integrating multiple ontology compared with existing mapping techniques.


[1] “A Survey of Schema-Based Matching Approaches”,Pavel Shvaiko and JérômeEuzenat, Journal on Data Semantics, Volume 3730, No.25, pp.146-171, 2005
[2] “A Novel Algorithm for Fully Automated Ontology Merging Using Hybrid Strategy”, Rene robin and G.V. Uma, European Journal of Scientific Research, Vol.47, No.1, pp.074-081, 2010.
[3] “Discrete particle swarm optimization for ontology alignment”,Jürgen Bock and Jan Hettenhausen, Information Sciences, Vol.192, No.4, pp.152–173. 2012.
[4] “Ontology alignment using machine learning techniques”,AzadehHaratian Nezhadi1, Bita Shadgar1 and AlirezaOsareh, International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 2, pp.39-45, 2011.
[5] “Ontology Integration for Linked DataLihua Zhao”, Ryutaro Ichise, Journal on Data Semantics, Volume.3, No.4, pp 237-254, 2014.
[6] “An Ontology Infrastructure for the Semantic”,DFensel, VrijeUniv, F. vanHarmelen, I. Horrocks ; D. L. McGuinness, P. F. Patel-Schneider, IEEE Intelligent systems, Vol.16, No.02 pp: 38-45, 2005.
[7] “Integrating Ontologies Based on P2P Mappings”, Ali I. El- Desouky, Sally M. El-Ghamrawy, Herminio Camargo de Souza, Jr., Ana Maria de C. Moura and Maria CláudiaCavalcanti, IEEE transactions on systems, man, and cybernetics-Part-A, VOL. 40, NO.5, pp. 1172-1185, 2010.
[8] “ASMOV: Ontology Alignment with Semantic Validation”, Yves R. Jean-Mary and Mansur R. Kabuka, Joint SWDB-ODBIS workshop, Vol. 125, pp.15-20, 2007.
[9] “Ontology Similarity Measure and Ontology Mapping via Learnig Optimization Similarity Function” Yun Gao and Wei Gao, International Journal of Machine Learning and Computing, Vol. 2, No. 2, April 2012.
[10] “QOM - Quick Ontology Mapping, Mapping”, Marc Ehrig and Steffen, The semantic Web-ISWC, Vol.3298, pp. 683-697, 2004.
[11] “R2O, an Extensible and Semantically based Database to Ontology Mapping”, LanguageJesúsBarrasaandÓscarCorcho, Proceedings of the second Workshop on Semantic Web and Databases, Vol.3272, pp.1069-1072, 2004.
[12] “Effectiveness of Automatic Translations for Cross- Lingual Ontology Mapping”, Mamoun Abu Helou, Matteo Palmonari, Mustafa Jarrar, Journal of Artificial Intelligence Research, Vol.12, No.4, pp.22-35, 2010.
[13] “Ontology mapping for erp business process Variations”, Artificial Intelligence Research, Vol.55, No.8, pp.165-208, 2016, VOL.24 , NO.8 , pp.1-6, 2013.
[14] “Configurable Translation-Based Cross-Lingual Ontology Mapping Systemto adjust Mapping”, Journal of Web semantic, VOL.10, NO.12, pp. 1-25, 2012.
[15] “Distributed multi-agent communication system based on dynamic ontology mapping”, Ali I. El-Desouky andSally M. El-Ghamrawy, Int. J. Communication Networks and Distributed Systems, Vol. 10, No.1, pp.1- 24, 2013.

This proposed method, perform better for integrating multiple ontology compared with existing mapping techniques.