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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2014: Intelligent Information and Database Systems pp 273–281Cite as

A New Method for Autocratic Decision Making Using Group Recommendations Based on Intervals of Linguistic Terms and Likelihood-Based Comparison Relations

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8398))

Abstract

This paper presents a new method for autocratic decision making using group recommendations based on intervals of linguistic terms and likelihood-based comparison relations. It can overcome the drawbacks of the existing methods for autocratic decision making using group recommendations. The proposed method provides us with a useful way for autocratic decision making using group recommendations based on intervals of linguistic terms and likelihood-based comparison relations.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

    Shyi-Ming Chen & Bing-Han Tsai

Authors
  1. Shyi-Ming Chen
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  2. Bing-Han Tsai
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Editor information

Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen  & Bogdan Trawiński  & 

  2. Faculty of Engineering, Department of Computer Engineering, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Boonwat Attachoo

  3. Software Engineering Program, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Kulwadee Somboonviwat

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Chen, SM., Tsai, BH. (2014). A New Method for Autocratic Decision Making Using Group Recommendations Based on Intervals of Linguistic Terms and Likelihood-Based Comparison Relations. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8398. Springer, Cham. https://doi.org/10.1007/978-3-319-05458-2_29

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  • DOI: https://doi.org/10.1007/978-3-319-05458-2_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05457-5

  • Online ISBN: 978-3-319-05458-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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