Abstract
In modern era, ontology integration is most prominent and challenging problem in various domains of data mining. It helps greatly on defining interoperability in information processing systems. Ontology integration institutes interoperability by deriving semantic similarity and correspondences between the entities of ontologies. Ontology matching plays an integral role in whole integration process by identifying the similarity measure between source and target ontologies using various matching techniques, e.g. Element-level techniques and Structure level techniques. The scope of this paper is to discuss existing ontology matching techniques and propose a multi-strategy ontology matching approach. In Proposed algorithm is a multi-strategy matching approach, where multiple similarity measure are combined and finally an ontology tree based on the binary tree is created. Ontology mapping is used for creating ontology binary tree. The hybrid approach of Ontology integration performs significantly better than its predecessor with single similarity measures.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Berners-Lee, T., Handler, J., Lassila, O.: The Semantic Web. Scientific American (2001)
Huiping, J.: Information retrieval and the Semantic Web. In: IEEE International Conference on Educational and Information Technology (ICEIT), vol. 3, pp. 461–463. Chongqing, China (2010)
Perez-Lopez, A., Blace, R. Fisher, M., Hebeler, J.: Semantic Web Programming. Wiley Publishing, Inc., New York (2009)
Huang, L., Hu, G., Yang, X.: Review of ontology mapping. In: 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), pp. 537–540. Yichang (2012)
Shvaiko, P., Euzenat, J.: Ontology matching: state of the art and future challenges. IEEE Trans. Knowl. Data. Eng. 25(1), 158–176 (2013)
Ye, B., Chai, H., He, W., Wang, X., Song, G.: Semantic similarity calculation method in ontology mapping. In: 2nd International Conference on Cloud Computing and Intelligent Systems (CCIS), vol. 3, pp. 1259–1262. Hangzhou (2012)
Xia, H., Zheng, X., Hu, X., Tian, Y.: Multi-strategy ontology mapping based on stacking method. In: Sixth International Conference on Fuzzy Systems and Knowledge Discovery (2009)
Fuqiang, L.,Yongfu, X.: The method of multi-strategy ontology mapping. In: ICCIS (2011)
Euzenat, E., Shvaiko, P.: Ontology Matching. Springer, Heidelberg (2013)
Rodrfguez, A., Egenhofer, M.: Determining semantic similarity among entity classes from diferent ontologies. IEEE Trans. Knowl. Data. Eng. 15(2), 442–456 (2003)
Li, C.M., Bo, S.J.: The research of ontology mapping method based on computing similarity. Sci. Technol. Inf. 1, 552–554 (2010)
Zhe, Y.: Semantic similarity match of ontology concept based on heuristic rules. Comput. Appl. 12 (2007)
Doan, A.H., Jayant, M., Pedro, D. et al.: Learning to map between ontologies on the semantic web. In: Eleventh International World Wide Web Conference, Honolulu Hawaii, USA (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer India
About this paper
Cite this paper
Kumar, S., Singh, V. (2015). Multi-strategy Based Matching Technique for Ontology Integration. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_12
Download citation
DOI: https://doi.org/10.1007/978-81-322-2202-6_12
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2201-9
Online ISBN: 978-81-322-2202-6
eBook Packages: EngineeringEngineering (R0)