A framework for ontology integration based on genetic algorithm
Authors: 
Lingyu Zhang, Bairui TaoAuthors Info & Claims
Lingyu Zhang, Bairui TaoAuthors Info & ClaimsPages 1643 - 1656
Abstract
Ontology integration is an important work when integrating information from heterogeneous ontologies into an ontology. The existing methods about ontology integration cannot effectively make full use of non-1-1 mappings, which are very common in the real world. Furthermore, these methods only stated that the concept-pairs with mappings should be integrated, but not gave the specific operations for it. Therefore, these methods cannot describe a complete framework for ontology integration. To this end, this paper proposes a framework for Ontology Integration based on Genetic Algorithm, called OI-GA. During the process of integrating ontologies, OI-GA firstly creates mappings between them based on similarity measures. Next, OI-GA finds out all the non-1-1 mappings from mappings, and provides an evolutionary method to extract 1-1 mappings from them. Finally, all the concepts belonging to different ontologies are integrated into a new knowledge base called integrated ontology. Experimental results indicate that OI-GA performs encouragingly well in the optimization of mapping set as well as in the integration of ontologies from the real world.
References
[1]
Alasoud A., Haarslev V. and Shiri N., A hybrid approach for ontology integration, in Proceedings of VLDB Workshop on Ontologies-based Techniques for DataBases and Information Systems (ODBIS) 2005, pp. 18–23.
[2]
Doan A., Madhavan J., Domingos P. and Halevy A., Learning to Map between Ontologies on the Semantic Web, in Proceedings of the Eleventh International World Wide Web Conference 2002, pp. 662–673.
[3]
Fang A., Hong N., Wu S., et al., An Integrated Biomedical Ontology Mapping Strategy Based on Multiple Mapping Methods, in Proceedings of Web Information Systems Engineering–WISE 2013 Workshops Springer, Berlin Heidelberg 2014, pp. 373–386.
[4]
Lange C., Ontologies and languages for representing mathematical knowledge on the semantic web, Semantic Web 4(2) (2013), 119–158.
[5]
Calvanese D., Giacomo G.D. and Lenzerini M., A framework for ontology integration, in proceedings of the 2001 Int Semantic Web Working Symposium 2001, pp. 303–316.
[6]
Jimenez-Ruiz E. and Cuenca Grau B., Horrocks I., et al., Ontology Integration Using Mappings: Towards Getting the Right Logical Consequences, in Proceedings of European Semantic Web Conference (ESWC), Volume 5554 of LNCS Springer-Verlag, 2009, pp. 173–187 .
[7]
Tang J., Li J.Z. and Liang B.Y., et al., RiMOM: A dynamic multistrategy ontology alignment framework, Knowledge and Data Engineering 21(8) (2008), 1218–1232.
[8]
Li L. and Yang Y., Agent-based ontology mapping and integration towards interoperability, Expert Systems 25(3) (2008), 197–220.
[9]
Zhang L.Y., Yan L. and Ma Z.M., A conceptual graph based approach for mappings among multiple fuzzy ontologies, Journal of Web Engineering 12(3-4) (2013), 215–231.
[10]
Tun N.N., Dong J.S. and Tojo S., A philosophy-driven entity classification and enrichment for ontology mapping, Expert Systems 28(2) (2011), 138–166.
[11]
Nguyen N.T. and Rusin M., A Consensus-Based Approach for Ontology Integration, in Proceedings of 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2006 Workshops) 2006, pp. 514–517.
[12]
Kutz O., Mossakowski T., Galinski C., et al., Towards a standard for heterogeneous ontology integration and interoperability, in Choi K.-S., et al., editors,First International Conference on Terminology, Language and Content Resources (LaRC) 2011, pp. 101–110.
[13]
Udrea O., Getoor L. and Miller R.J., Leveraging data and structure in ontology integration, in Proceedigns of the 2007 ACM SIGMOD International Conference on Management of Data 2007, pp. 449–460.
[14]
Haase P., Horrocks I., Hovland D., et al., Optique System: Towards Ontology and Mapping Management in OBDA Solutions, in Proceedings of the Second International Workshop on Debugging Ontologies and Ontology Mappings-WoDOOM13 2013, pp. 21–32.
[15]
Sofia P.H., Gomez-Perez A. and Martins J.P., Some Issues on Ontology Integration, in proceedings of IJCAI99’s Workshop on Ontologies and Problem Solving Methods: Lessons Learned and Future Trends 1999.
[16]
Lambrix P. and Tan H., SAMBO-a system for aligning and merging biomedical ontologies, Journal of Web Semantics: Science, Services and Agents on the World Wide Web 4(3) (2006), 196–206.
[17]
Vasant P.M., Handbook of Research on Artificial Intelligence Techniques and Algorithms, Hershey, PA: IGI Global, https://doi.org/10.4018/978-1-4666-7258-1.
[18]
Vasan P.M., Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications, Hershey, PA: IGI Global, 1–1018 https://doi.org/10.4018/978-1-4666-4450-2.
[19]
Studer R., Benjamins V.R. and Fensel D., Knowledge engineering: Principles and methods, Data and Knowledge Engineering 25(1-2) (1998), 161–197.
[20]
Kumar S.K. and Harding J.A., Ontology mapping using description logic and bridging axioms, Computers in Industry 64(1) (2013), 19–28.
[21]
Heer T., Retkowitz D. and Kraft B., Algorithm and tool for ontology integration based on graph rewriting, in proceedings of Applications of Graph Transformations with Industrial Relevance (AGTIVE), Wilhelmshöhe, Kassel, Germany 2007, pp. 484–490.
[22]
Duong T.H., Nguyen N.T. and Jo G.S., A hybrid method for integrating multiple ontologies, Cybernetics and Systems 40(2) (2009), 123–145.
[23]
Qazvinian V., Abolhassani H., Haeri S.H., et al., Evolutionary coincidence-based ontology mapping extraction, Expert Systems 25(3) (2008), 221–236.
[24]
Biletskiy Y., Ranganathan G.R. and Vorochek O., Identification and resolution of conflicts during ontological integration using rules, Expert Systems 27(2) (2010), 75–89.
[25]
Liang Y., Hong B. and Liu H., Hybrid Ontology Integration for Distributed System, in proceedings of the Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2007, pp. 309–314.
[26]
Li Z., Qing Y. and Wei C., Research on Ontology Integration Combined with Machine learning, in Proceedings of International Conference on Intelligent Computation Technology and Automation, 2009, pp. 464–467.
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Published: 01 January 2016
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