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International Conference on Computational Collective Intelligence

ICCCI 2014: Computational Collective Intelligence. Technologies and Applications pp 414–423Cite as

A Consensus-Based Method for Solving Concept-Level Conflict in Ontology Integration

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8733))

Abstract

Ontology reuse has been an important factor in developing shared knowledge in Semantic Web. The ontology reuse enables knowledge sharing more easily between intelligent ontology-based systems. However, this cannot completely reduce conflict potentials in ontology integration. This paper presents a method based on the consensus theory and a evaluation function of similarity measure between concepts which is used for a proposed algorithm for ontology integration at the concept level.

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References

  1. Barthélemy, J.-P., Janowitz, M.F.: A formal theory of consensus. SIAM Journal on Discrete Mathematics 4(3), 305–322 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  2. Duong, T.H., Nguyen, N.T., Kozierkiewicz-Hetmanska, A., Jo, G.: Fuzzy ontology integration using consensus to solve conflicts on concept level. In: ACIIDS Posters, pp. 33–42 (2011)

    Google Scholar 

  3. Euzenat, J., Shvaiko, P.: Ontology Matching, Second Edition. 2, pp. 1–511. Springer, Heidelberg (2013)

    Book  Google Scholar 

  4. Fareh, M., Boussaid, O., Chalal, R., Mezzi, M., Nadji, K.: Merging ontology by semantic enrichment and combining similarity measures. International Journal of Metadata, Semantics and Ontologies 8(1), 65–74 (2013)

    Article  Google Scholar 

  5. Ge, J., Qiu, Y.: Concept similarity matching based on semantic distance. In: Fourth International Conference on Semantics, Knowledge and Grid, SKG 2008, pp. 380–383. IEEE (2008)

    Google Scholar 

  6. Nguyen, N.T.: Representation choice methods as the tool for solving uncertainty in distributed temporal database systems with indeterminate valid time. In: Monostori, L., Váncza, J., Ali, M. (eds.) IEA/AIE 2001. LNCS (LNAI), vol. 2070, pp. 445–454. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  7. Nguyen, N.T.: Advanced methods for inconsistent knowledge management. Springer (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. College of Sciences, Hue University, 77 Nguyen Hue Street, Hue City, Vietnam

    Trung Van Nguyen

  2. Hue University, 3 Le Loi Street, Hue City, Vietnam

    Hanh Huu Hoang

Authors
  1. Trung Van Nguyen
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  2. Hanh Huu Hoang
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Yeungnam University, Korea

    Dosam Hwang  & Jason J. Jung  & 

  2. Institute of Informatics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc-Thanh Nguyen

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Van Nguyen, T., Hoang, H.H. (2014). A Consensus-Based Method for Solving Concept-Level Conflict in Ontology Integration. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_42

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  • DOI: https://doi.org/10.1007/978-3-319-11289-3_42

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11288-6

  • Online ISBN: 978-3-319-11289-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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