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Automatic ontology construction based on clustering nucleus

  • Computer Science
  • Published:
Wuhan University Journal of Natural Sciences

Abstract

Ontology construction is the core task of ontology-based knowledge representation. This paper explores a semantic description approach based on primitive structure, which benefits ontological relation description in a more precise and concrete way. In view of primitive structure, this paper introduces an approach to extract primitive structures of words based on a multi-label learning model, correlated label propagation. Also, this paper proposes an approach to recognize clustering nucleuses in word clusters heuristically. By this approach, more precise ontological relations are able to be discovered automatically.

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Authors and Affiliations

  1. School of Foreign Languages and Literature, Wuhan University, Wuhan, 430072, Hubei, China

    Ling Zhao & Han Ren

  2. Hubei Research Establishment of Language and Intelligent Information Processing, Wuhan University, Wuhan, 430072, Hubei, China

    Ling Zhao, Han Ren & Jing Wan

Authors
  1. Ling Zhao
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  2. Han Ren
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  3. Jing Wan
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Corresponding author

Correspondence to Han Ren.

Additional information

Foundation item: Supported by the National Natural Science Foundation of China (61402341, 61173095, 61173062), the Major Projects of National Social Science Foundation of China (11&ZD189) and the China Postdoctoral Science Foundation Funded Project (2014M552073)

Biography: ZHAO Ling, female, Associate professor, Ph.D., research direction: applied linguistics and Chinese information processing.

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Zhao, L., Ren, H. & Wan, J. Automatic ontology construction based on clustering nucleus. Wuhan Univ. J. Nat. Sci. 20, 129–133 (2015). https://doi.org/10.1007/s11859-015-1070-4

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  • DOI: https://doi.org/10.1007/s11859-015-1070-4

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