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International Symposium on Methodologies for Intelligent Systems

ISMIS 2018: Foundations of Intelligent Systems pp 247–257Cite as

Exploiting Order Information Embedded in Ordered Categories for Ordinal Data Clustering

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11177))

Abstract

As a major type of categorical data, ordinal data are those with the attributes whose possible values (also called categories interchangeably) are naturally ordered. As far as we know, all the existing distance metrics proposed for categorical data do not take the underlying order information into account during the distance measurement. This will make the produced distance incorrect and will further influence the results of ordinal data clustering. We therefore propose a specially designed distance metric, which can exploit the order information embedded in the ordered categories for distance measurement. It quantifies the distance between two ordinal categories by accumulating the sub-entropies of all the categories ordered between them. Since the proposed distance metric takes the order information into account, distance produced by it will be more reasonable than the other metrics proposed for categorical data. Moreover, it is parameter-free and can be easily applied to different ordinal data clustering tasks. Experimental results show the promising advantages of the proposed distance metric.

This work was fully supported by Faculty Research Grant of Hong Kong Baptist University under Project FRG2/17-18/082.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China

    Yiqun Zhang & Yiu-ming Cheung

  2. HKBU Institute of Research and Continuing Education, Shenzhen, China

    Yiu-ming Cheung

Authors
  1. Yiqun Zhang
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  2. Yiu-ming Cheung
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Corresponding author

Correspondence to Yiu-ming Cheung .

Editor information

Editors and Affiliations

  1. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. American University, Washington, DC, USA

    Nathalie Japkowicz

  3. Hong Kong Baptist University, Kowloon, Hong Kong

    Jiming Liu

  4. University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  5. University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Raś

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Zhang, Y., Cheung, Ym. (2018). Exploiting Order Information Embedded in Ordered Categories for Ordinal Data Clustering. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2018. Lecture Notes in Computer Science(), vol 11177. Springer, Cham. https://doi.org/10.1007/978-3-030-01851-1_24

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  • DOI: https://doi.org/10.1007/978-3-030-01851-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01850-4

  • Online ISBN: 978-3-030-01851-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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