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Management of Information Incompleteness in Rough Non-deterministic Information Analysis

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Advances on Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 297))

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Abstract

Rough Non-deterministic Information Analysis (RNIA) is a mathematical framework for handling tables with exact and inexact data. Within this framework, we are developing algorithms aimed at rule generation and direct question-answering. In this paper, we investigate different forms and interpretations of data incompleteness, and show how algorithms implemented in RNIA manipulate them.

The first author is supported by the Grant-in-Aid for Scientific Research (C) (No.22500204), Japan Society for the Promotion of Science. The third author is supported by the grants N N516 077837 and 2011/01/B/ST6/03867 from the Ministry of Science and Higher Education of the Republic of Poland, and the National Centre for Research and Development (NCBiR) under the grant SP/I/1/77065/10 by strategic scientific research and experimental development program: “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.

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Author information

Authors and Affiliations

  1. Mathematical Sciences Section, Department of Basic Sciences, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, 804, Japan

    Hiroshi Sakai

  2. Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba, 283, Japan

    Michinori Nakata

  3. Institute of Mathematics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  4. Infobright Inc., Poland, Krzywickiego 34 pok. 219, 02-078, Warsaw, Poland

    Dominik Ślęzak

Authors
  1. Hiroshi Sakai
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  2. Michinori Nakata
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  3. Dominik Ślęzak
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. Université Pierre et Marie Curie - Paris6, CNRS UMR 7606, DAPA, LIP6 8, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute, IONA College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Sakai, H., Nakata, M., Ślęzak, D. (2012). Management of Information Incompleteness in Rough Non-deterministic Information Analysis. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_29

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  • DOI: https://doi.org/10.1007/978-3-642-31709-5_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31708-8

  • Online ISBN: 978-3-642-31709-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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