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2M-SELAR: A Model for Mining Sequential Least Association Rules

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Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 520))

Abstract

Recently, mining least association rule from the sequential data becomes more important in certain domain areas such as education, healthcare, text mining, etc. due to its uniqueness and usefulness. However, discovering such rule is a great challenge because it involves with a set of least items which usually holds a very low in term of support. Therefore, in this paper propose a model for mining sequential least association rule (2M-SELAR) that embedded with SELAR algorithm, and Critical Relative Support (CRS) and Definite Factor (DF) measures. The experimental results reveal that 2M-SELAR can successfully generate the desired rule from the given datasets.

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Author information

Authors and Affiliations

  1. School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030, Kuala Terengganu, Malaysia

    Zailani Abdullah, Omer Adam & Md Yazid Mohd Saman

  2. Faculty of Computer Science & Information Technology, Universiti Malaya, 50603, Kuala Lumpur, Malaysia

    Tutut Herawan

  3. Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300, Kuantan, Pahang, Malaysia

    Ahmad Noraziah

  4. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Abdul Razak Hamdan

Authors
  1. Zailani Abdullah
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  2. Omer Adam
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  3. Tutut Herawan
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  4. Ahmad Noraziah
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  5. Md Yazid Mohd Saman
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  6. Abdul Razak Hamdan
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Corresponding author

Correspondence to Zailani Abdullah .

Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia

    Mohamed Othman

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

    Rozaida Ghazali

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

    Mustafa Mat Deris

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

    Hairulnizam Mahdin

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

    Tutut Herawan

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Abdullah, Z., Adam, O., Herawan, T., Noraziah, A., Saman, M.Y.M., Hamdan, A.R. (2019). 2M-SELAR: A Model for Mining Sequential Least Association Rules. In: Abawajy, J., Othman, M., Ghazali, R., Deris, M., Mahdin, H., Herawan, T. (eds) Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) . Lecture Notes in Electrical Engineering, vol 520. Springer, Singapore. https://doi.org/10.1007/978-981-13-1799-6_10

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