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Super Attribute Representative for Decision Attribute Selection

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 180))

Abstract

Soft set theory proposed by Molodstov is a general mathematic tool for dealing with uncertainties. Recently, several algorithms had been proposed for decision making using soft set theory. However, these algorithms still concern on a Boolean-valued information system. In this paper, Support Attribute Representative (SAR), a soft set based technique for decision making in categorical-valued information system is proposed. The proposed technique has been tested on two datasets. The results of this research will provide useful information for decision makers to handle categorical datasets.

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© 2011 Springer-Verlag Berlin Heidelberg

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Mamat, R., Herawan, T., Mat Deris, M. (2011). Super Attribute Representative for Decision Attribute Selection. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22191-0_12

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  • DOI: https://doi.org/10.1007/978-3-642-22191-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22190-3

  • Online ISBN: 978-3-642-22191-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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