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A New Semantic Model for Domain-Ontology Learning

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Human Centered Computing (HCC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8944))

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Abstract

Nowadays, ontology has been widely used in computer science. With the rapid development of it, Ontology Learning (OL) becomes one of the main research topics. However, with the current technology, all existing OL (from unstructured data source) methods rely on predefined knowledge about a specific domain. In this case, it’s more like an ontology enrichment process rather than a learning process. In this paper, a new learning model will be introduced. Rather than working on language level, this new approach focusing on structure level and trying to identify why and how a particular structure can represent a specific thing. Therefore, it allows the OL process not to rely on the predefined knowledge about a specific domain which people want to build an ontology for.

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Author information

Authors and Affiliations

  1. School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK

    Jizheng Wan & John Barnden

  2. Corporate ICT, Birmingham City University, Birmingham, B42 2SU, UK

    Jizheng Wan

Authors
  1. Jizheng Wan
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  2. John Barnden
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Corresponding author

Correspondence to Jizheng Wan .

Editor information

Editors and Affiliations

  1. Wuhan University of Technology, Wuhan, China

    Qiaohong Zu

  2. Fujitsu Laboratories of Europe, Middlesex, United Kingdom

    Bo Hu

  3. Fudan University, Shanghai, China

    Ning Gu

  4. Telecommunications and Information Communication Technology, National Institute of Posts, Phnom Penh, Cambodia

    Sopheap Seng

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Wan, J., Barnden, J. (2015). A New Semantic Model for Domain-Ontology Learning. In: Zu, Q., Hu, B., Gu, N., Seng, S. (eds) Human Centered Computing. HCC 2014. Lecture Notes in Computer Science(), vol 8944. Springer, Cham. https://doi.org/10.1007/978-3-319-15554-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-15554-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15553-1

  • Online ISBN: 978-3-319-15554-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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