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Mining Indirect Least Association Rule

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Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 285))

Abstract

Indirect pattern can be considered as one of the interesting information that is hiding in transactional database. It corresponds to the property of high dependencies between two items that are rarely appeared together but indirectly occurred through another items. Therefore, we propose an algorithm for Mining Indirect Least Association Rule (MILAR) from the real dataset. MILAR is embedded with a scalable least measure called Critical Relative Support (CRS). The experimental results indicate that MILAR is capable in generating the indirect least association rules from the given dataset.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Universiti Malaysia Terengganu, Kuala Terengganu, Malaysia

    Zailani Abdullah

  2. Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  3. Universitas Teknologi Yogyakarta, Yogyakarta, Indonesia

    Tutut Herawan

  4. Faculty of Science Computer and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

Authors
  1. Zailani Abdullah
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  2. Tutut Herawan
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  3. Mustafa Mat Deris
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Corresponding author

Correspondence to Zailani Abdullah .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

  3. School of Information Technology, Deakin University, Burwood, Victoria, Australia

    Jemal Abawajy

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Abdullah, Z., Herawan, T., Mat Deris, M. (2014). Mining Indirect Least Association Rule. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_19

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  • DOI: https://doi.org/10.1007/978-981-4585-18-7_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-4585-17-0

  • Online ISBN: 978-981-4585-18-7

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