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MB Based Multi-dividing Ontology Learning Trick

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Data Mining and Big Data (DMBD 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1453))

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Abstract

The conceptual structure of the ontology is usually represented by a graph, and the related information of this concept is encapsulated by a vector with uniform dimension. The essence of the similarity calculation of the ontology concept is the calculation of the distance of the vector corresponding to the vertex in the high-dimensional space. This paper continues to consider the ontology learning algorithm of the multi-dividing setting, and proposes a MB based learning strategy under this framework. The experimental data verifies the effectiveness of the given new algorithm.

The research is partially supported by NSFC (no. 11761083).

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Author information

Authors and Affiliations

  1. School of Information Engineering, Qujing Normal University, Qujing, 6655011, China

    Meihui Lan

  2. School of Information Science and Technology, Yunnan Normal University, Kunming, 650500, China

    Wei Gao

Authors
  1. Meihui Lan
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  2. Wei Gao
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Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. The University of Sydney, Sydney, Australia

    Albert Zomaya

  4. Guangzhou University, Guangzhou, China

    Hongyang Yan

  5. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

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Lan, M., Gao, W. (2021). MB Based Multi-dividing Ontology Learning Trick. In: Tan, Y., Shi, Y., Zomaya, A., Yan, H., Cai, J. (eds) Data Mining and Big Data. DMBD 2021. Communications in Computer and Information Science, vol 1453. Springer, Singapore. https://doi.org/10.1007/978-981-16-7476-1_4

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  • DOI: https://doi.org/10.1007/978-981-16-7476-1_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7475-4

  • Online ISBN: 978-981-16-7476-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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