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Design of Learning Ontology Framework Based Text

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Emerging Research in Web Information Systems and Mining (WISM 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 238))

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Abstract

In this text give a learning ontology framework. The framework includes term extraction, ontology building and ontology pruning three function modules. Term extraction can identify words in the web text that are relevant for ontology building; Ontology building can automatism build ontology bases extract terms, In the build ontology process we give a automatism build ontology method base ontel, this method can solve some ontology learning methods can’t completely learning relations between different concepts; Ontology pruning filters out some irrelevant concepts and redundancy concepts, so we can capture a prefect domain ontology.

This paper supported by NSFC(60875081).

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Author information

Authors and Affiliations

  1. School of Computer and Information Engineering, Anyang Normal University, Ayyang, Henan, China

    Wu Qin-xia & Liu Yong-ge

Authors
  1. Wu Qin-xia
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  2. Liu Yong-ge
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Taipa, Macau, China

    Gong Zhiguo

  2. School of Computer, Shanghai University, 200444, Shanghai, China

    Xiangfeng Luo

  3. School of Computer and Software, Taiyuan University of Technology, 030024, Taiyuan, China

    Junjie Chen

  4. Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan, Hong Kong SAR, China

    Fu Lee Wang

  5. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

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© 2011 Springer-Verlag Berlin Heidelberg

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Qin-xia, W., Yong-ge, L. (2011). Design of Learning Ontology Framework Based Text. In: Zhiguo, G., Luo, X., Chen, J., Wang, F.L., Lei, J. (eds) Emerging Research in Web Information Systems and Mining. WISM 2011. Communications in Computer and Information Science, vol 238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24273-1_17

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  • DOI: https://doi.org/10.1007/978-3-642-24273-1_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24272-4

  • Online ISBN: 978-3-642-24273-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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