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A Model of User-Oriented Reduct Construction Based on Minimal Set Cover

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Data and Knowledge Engineering (ICDKE 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7696))

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Abstract

An implicit assumption of many learning algorithm is that all attributes in the attribute set are of the same importance. However, this assumption is unreasonable or practical. If attributes in the attribute set are considered of non-equal importance with respect to their own situation, then the model obtained from those attributes would be more realistic. This paper designed a user oriented reduction model based on the minimal set cover by seamlessly combining an order of attributes that describes user preferences. The accessibility and efficiency of this algorithm is shown by an example.

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Author information

Authors and Affiliations

  1. Computer Science and Technology Department, Taiyuan Normal University TYNU, Shanxi, Taiyuan, China

    Suqing Han & Guimei Yin

Authors
  1. Suqing Han
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  2. Guimei Yin
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Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, 3125, Burwood, VIC, Australia

    Yang Xiang

  2. Media Distribution, Telstra Corporation Limited, 21/35 Collins St, 3000, Melbourne, VIC, Australia

    Mukaddim Pathan

  3. Department of Mathematics and Computing, The University of Southern Queensland, Toowoomba, QLD, Australia

    Xiaohui Tao

  4. Department of Mathematics and Computing, The University of Southern Queensland, Toowoomba, QLD, Australia

    Hua Wang

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© 2012 Springer-Verlag Berlin Heidelberg

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Han, S., Yin, G. (2012). A Model of User-Oriented Reduct Construction Based on Minimal Set Cover. In: Xiang, Y., Pathan, M., Tao, X., Wang, H. (eds) Data and Knowledge Engineering. ICDKE 2012. Lecture Notes in Computer Science, vol 7696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34679-8_10

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  • DOI: https://doi.org/10.1007/978-3-642-34679-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34678-1

  • Online ISBN: 978-3-642-34679-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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