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Ordinal Assessment of Data Consistency Based on Regular Expressions

  • Conference paper
  • First Online:
Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 611))

Abstract

In this paper, a novel assessment method for measurement of consistency of individual, text-valued attributes is proposed. The first novelty of this method is that it allows to express a broad range of well-known consistency measurements in a simple, elegant and standardized way. This property is obtained by relying on the standardized framework of regular expressions to support measurement. The key advantage of using such a highly standardized expression syntax, is that knowledge about consistency becomes portable, exchangeable and easy to access. The second novelty of the method, is that it examines the advantages of using a finite and ordinal scale for expression of measurement. These advantages include a high degree of interpretation and efficient calculations both in terms of time and space complexity.

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Notes

  1. 1.

    This example is fictional.

  2. 2.

    Such a paradigm is also used to determine the normal form of a relational database [5, 6].

  3. 3.

    The assignment of indices to groups is standardized and is a based on the order in which opening brackets appear in the pattern.

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Author information

Authors and Affiliations

  1. Department of Telecommunication and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000, Ghent, Belgium

    Antoon Bronselaer, Joachim Nielandt, Robin De Mol & Guy De Tré

Authors
  1. Antoon Bronselaer
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  2. Joachim Nielandt
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  3. Robin De Mol
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  4. Guy De Tré
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Corresponding author

Correspondence to Antoon Bronselaer .

Editor information

Editors and Affiliations

  1. INESC-ID,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Joao Paulo Carvalho

  2. LIP 6, Université Pierre et Marie Curie, Paris, France

    Marie-Jeanne Lesot

  3. School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Uzay Kaymak

  4. IDMEC,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Susana Vieira

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Iona College, Machine Intelligence Institute, New Rochelle, New York, USA

    Ronald R. Yager

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© 2016 Springer International Publishing Switzerland

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Bronselaer, A., Nielandt, J., De Mol, R., De Tré, G. (2016). Ordinal Assessment of Data Consistency Based on Regular Expressions. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-40581-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-40581-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40580-3

  • Online ISBN: 978-3-319-40581-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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