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Rough Sets in Hybrid Soft Computing Systems

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Advanced Data Mining and Applications (ADMA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4632))

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Abstract

Soft computing is considered as a good candidate to deal with imprecise and uncertain problems in data mining. In the last decades research on hybrid soft computing systems concentrates on the combination of fuzzy logic, neural networks and genetic algorithms. In this paper a survey of hybrid soft computing systems based on rough sets is provided in the field of data mining. These hybrid systems are summarized according to three different functions of rough sets: preprocessing data, measuring uncertainty and mining knowledge. General observations about rough sets based hybrid systems are presented. Some challenges of existing hybrid systems and directions for future research are also indicated.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Ludong University, Yantai 264025, China

    Renpu Li, Yongsheng Zhao, Fuzeng Zhang & Lihua Song

Authors
  1. Renpu Li
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  2. Yongsheng Zhao
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  3. Fuzeng Zhang
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  4. Lihua Song
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Editor information

Editors and Affiliations

  1. Computer Science Department, University of Calgary , Calgary, AB, Canada

    Reda Alhajj

  2. School of Computer Science and Technology , Harbin Institute of Technology, Harbin, China

    Hong Gao

  3. School of Computer Science and Technology , Harbin Institute of Technology , Harbin, China

    Jianzhong Li

  4. School of Information Technology and Electronic Engineering , The University of Queensland , Queensland, Australia

    Xue Li

  5. Department of Computing Science , University of Alberta, Edmonton, AB, Canada

    Osmar R. Zaïane

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© 2007 Springer Berlin Heidelberg

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Li, R., Zhao, Y., Zhang, F., Song, L. (2007). Rough Sets in Hybrid Soft Computing Systems. In: Alhajj, R., Gao, H., Li, J., Li, X., Zaïane, O.R. (eds) Advanced Data Mining and Applications. ADMA 2007. Lecture Notes in Computer Science(), vol 4632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73871-8_5

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  • DOI: https://doi.org/10.1007/978-3-540-73871-8_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73870-1

  • Online ISBN: 978-3-540-73871-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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