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Advanced Computational Methods for Knowledge Engineering pp 343–354Cite as

An Approach to Semantic Indexing Based on Tolerance Rough Set Model

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 479))

Abstract

In this article we propose a general framework incorporating semantic indexing and search of texts within scientific document repositories, where document representation may include, excepts the content, some additional document meta-data, citations and semantic information. Our idea is based on application of Tolerance Rough Set Model, semantic information extracted from source text and domain ontology to approximate concepts associated with documents and to enrich the vector representation. We present the experiment performed over the freely accessed biomedical research articles from Pubmed Cetral (PMC) portal. The experimental results are showing the advantages of the proposed solution.

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Author information

Authors and Affiliations

  1. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Sinh Hoa Nguyen

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Hung Son Nguyen

Authors
  1. Sinh Hoa Nguyen
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  2. Hung Son Nguyen
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Corresponding author

Correspondence to Sinh Hoa Nguyen .

Editor information

Editors and Affiliations

  1. , Division of Knowledge Management Systems, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, Wroclaw, 50-370, Poland

    Ngoc Thanh Nguyen

  2. and Economics, Department of Telecommunications, Budapest University of Technology, Pazmany Peter setany 1/D, Budapest, 1111, Hungary

    Tien van Do

  3. LITA - UFR MIM, Université de Lorraine – Metz, Ile du Saulcy, Metz Cedex 01, 57045, France

    Hoai An le Thi

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© 2013 Springer International Publishing Switzerland

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Nguyen, S.H., Nguyen, H.S. (2013). An Approach to Semantic Indexing Based on Tolerance Rough Set Model. In: Nguyen, N., van Do, T., le Thi, H. (eds) Advanced Computational Methods for Knowledge Engineering. Studies in Computational Intelligence, vol 479. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00293-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-00293-4_26

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00292-7

  • Online ISBN: 978-3-319-00293-4

  • eBook Packages: EngineeringEngineering (R0)

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