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Dominance-Based Soft Set Approach in Decision-Making Analysis

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Advanced Data Mining and Applications (ADMA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7120))

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Abstract

Multi-criteria decision analysis, sometimes called multi-criteria decision making, is a discipline aimed at supporting decision makers faced with making numerous and sometimes conflicting evaluations. Multi-criteria decision analysis aims at highlighting these conflicts and providing a compromised solution in a transparent process. This paper introduces the application of soft-dominance relation based on soft set theory in the field of multi-criteria decision analysis. This relation is an extension of the soft set theory which deals with typical inconsistencies during the consideration of criteria and in preference-ordered decision classes. The paper also utilized soft-dominance relations based on soft set theory in obtaining the decision rules in dealing with problems in a multi-valued information system.

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Author information

Authors and Affiliations

  1. Faculty of Informatics, Universiti Sultan Zainal Abidin, Terengganu, Malaysia

    Awang Mohd Isa & Ahmad Nazari Mohd Rose

  2. Faculty of Information Technology and Multimedia, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Mustafa Mat Deris

Authors
  1. Awang Mohd Isa
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  2. Ahmad Nazari Mohd Rose
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  3. Mustafa Mat Deris
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China

    Jie Tang  & Jianyong Wang  & 

  2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, SAR, China

    Irwin King

  3. Faculty of Engineering and Information Technology, University of Technology, 2007, Sydney, NSW, Australia

    Ling Chen

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© 2011 Springer-Verlag Berlin Heidelberg

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Isa, A.M., Rose, A.N.M., Deris, M.M. (2011). Dominance-Based Soft Set Approach in Decision-Making Analysis. In: Tang, J., King, I., Chen, L., Wang, J. (eds) Advanced Data Mining and Applications. ADMA 2011. Lecture Notes in Computer Science(), vol 7120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25853-4_23

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  • DOI: https://doi.org/10.1007/978-3-642-25853-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25852-7

  • Online ISBN: 978-3-642-25853-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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