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ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 549))

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Abstract

Most of the algorithm and data structure facing a computational problem when they are required to deal with a highly sparse and dense dataset. Therefore, in this paper we proposed a complete model for mining least patterns known as Efficient Least Pattern Mining Model (ELP-M2) with LP-Tree data structure and LP-Growth algorithm. The comparative study is made with the well-know LP-Tree data structure and LP-Growth algorithm. Two benchmarked datasets from FIMI repository called Kosarak and T40I10D100K were employed. The experimental results with the first and second datasets show that the LP-Growth algorithm is more efficient and outperformed the FP-Growth algorithm at 14% and 57%, respectively.

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Acknowledgement

This work is supported by the research grant from Research Acceleration Center Excellence (RACE) of Universiti Kebangsaan Malaysia.

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Authors and Affiliations

  1. Faculty of Entrepreneurship and Business / Centre of Computing and Informatics, Universiti Malaysia Kelantan, 16100, Kota Bharu, Kelantan, Malaysia

    Zailani Abdullah

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

    Amir Ngah

  3. Faculty of Computer Science and Information Technology, Universiti Malaya, 50603, Kuala Lumpur, Malaysia

    Tutut Herawan

  4. Faculty of Computer System and Software Engineering, Universiti Malaysia Pahang Malaysia, 26300, Kuantan, Pahang, Malaysia

    Noraziah Ahmad

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

    Siti Zaharah Mohamad & Abdul Razak Hamdan

Authors
  1. Zailani Abdullah
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  2. Amir Ngah
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  3. Tutut Herawan
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  4. Noraziah Ahmad
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  5. Siti Zaharah Mohamad
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  6. Abdul Razak Hamdan
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Corresponding author

Correspondence to Zailani Abdullah .

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Editors and Affiliations

  1. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Rozaida Ghazali

  3. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Nazri Mohd Nawi

  4. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

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Abdullah, Z., Ngah, A., Herawan, T., Ahmad, N., Mohamad, S.Z., Hamdan, A.R. (2017). ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_23

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