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Argumentation Based Ontology Alignment Extraction

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Advanced Machine Learning Technologies and Applications (AMLTA 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1339))

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Abstract

The ontology matching technique aims at establishing the correspondence between two ontologies’ entities to solve their heterogeneity problem. In the matching process, the quality of the single matcher’s alignment can not be ensured. Usually, multiple matches are required to work together to increase the evidence of potential matches or mismatches. Selecting, combining, and adjusting these ontology matches to obtain high-quality ontology comparisons is one of the main challenges in ontology matching. This paper proposes an Argumentation Framework (A.F.) based on the ontology extracting technique to address this challenge. First, the proposed approach obtains the alignments obtained by different ontology matches. It extracts the final alignment by debating the disputed entity correspondences with A.F. The experiment is conducted on the Bibliographic track provided by Ontology Alignment Evaluation Initiative (OAEI), and the statistical comparison with the state-of-the-art ontology matching techniques shows the effectiveness of the proposed approach.

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Acknowledgment

This work is supported by the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments (No. YQ20206), the Program for New Century Excellent Talents in Fujian Province University (No. GY-Z18155), the Scientific Research Foundation of Fujian University of Technology (No. GY-Z17162), the Science and Technology Planning Project in Fuzhou City (No. 2019-G-40), the Foreign Cooperation Project in Fujian Province (No. 2019I0019) and Sub-project of the National Key R&D Program of the Ministry of Science and Technology (2018YFC1201103).

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Authors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, 33 Xuefu South Road, Fuzhou, 350118, Fujian, China

    Xiaojing Wu & Xingsi Xue

  2. Intelligent Information Processing Research Center, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Xingsi Xue

  3. Institute of Artificial Intelligence, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Xingsi Xue

  4. Fujian Key Lab for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Xingsi Xue

  5. School of Information Science and Engineering, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Wenyu Hu

Authors
  1. Xiaojing Wu
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  2. Xingsi Xue
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  3. Wenyu Hu
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Corresponding author

Correspondence to Xingsi Xue .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Computer and Information Faculty, Giza, Egypt

    Aboul-Ella Hassanien

  2. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Kuo-Chi Chang

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Tang Mincong

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Wu, X., Xue, X., Hu, W. (2021). Argumentation Based Ontology Alignment Extraction. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_96

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