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

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

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 stru...

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Main Authors: Zailani, Abdullah, Amir, Ngah, Herawan, Tutut, Noraziah, Ahmad, Siti Zaharah, Mohamad, Abdul Razak, Hamdan
Format: Book Section
Language:English
English
Published: Springer 2017
Subjects:
Q Science (General)
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/1/book%20chapter1.pdf
http://umpir.ump.edu.my/id/eprint/16627/7/3.%20ELP%20M2%20An%20Efficient%20Model%20for%20Mining%20Least%20Patterns%20from%20Data%20Repository.pdf
id ump-16627
recordtype eprints
spelling ump-166272018-10-16T08:23:26Z http://umpir.ump.edu.my/id/eprint/16627/ ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository Zailani, Abdullah Amir, Ngah Herawan, Tutut Noraziah, Ahmad Siti Zaharah, Mohamad Abdul Razak, Hamdan Q Science (General) QA Mathematics 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. Springer Herawan, Tutut Rozaida, Ghazali Nazri, Mohd Nawi Mustafa, Mat Deris 2017 Book Section PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/16627/1/book%20chapter1.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/16627/7/3.%20ELP%20M2%20An%20Efficient%20Model%20for%20Mining%20Least%20Patterns%20from%20Data%20Repository.pdf Zailani, Abdullah and Amir, Ngah and Herawan, Tutut and Noraziah, Ahmad and Siti Zaharah, Mohamad and Abdul Razak, Hamdan (2017) ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository. In: Recent Advances on Soft Computing and Data Mining: The Second International Conference on Soft Computing and Data Mining (SCDM-2016), Bandung, Indonesia, August 18-20, 2016 Proceedings. Advances in Intelligent Systems and Computing (AISC), 549 . Springer, Cham, pp. 224-232. ISBN 978-3-319-51279-2 http://dx.doi.org/10.1007/978-3-319-51281-5_23 doi: 10.1007/978-3-319-51281-5_23
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic Q Science (General)
QA Mathematics
spellingShingle Q Science (General)
QA Mathematics
Zailani, Abdullah
Amir, Ngah
Herawan, Tutut
Noraziah, Ahmad
Siti Zaharah, Mohamad
Abdul Razak, Hamdan
ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
description 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.
author2 Herawan, Tutut
author_facet Herawan, Tutut
Zailani, Abdullah
Amir, Ngah
Herawan, Tutut
Noraziah, Ahmad
Siti Zaharah, Mohamad
Abdul Razak, Hamdan
format Book Section
author Zailani, Abdullah
Amir, Ngah
Herawan, Tutut
Noraziah, Ahmad
Siti Zaharah, Mohamad
Abdul Razak, Hamdan
author_sort Zailani, Abdullah
title ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
title_short ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
title_full ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
title_fullStr ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
title_full_unstemmed ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
title_sort elp-m2: an efficient model for mining least patterns from data repository
publisher Springer
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/
http://umpir.ump.edu.my/id/eprint/16627/1/book%20chapter1.pdf
http://umpir.ump.edu.my/id/eprint/16627/7/3.%20ELP%20M2%20An%20Efficient%20Model%20for%20Mining%20Least%20Patterns%20from%20Data%20Repository.pdf
first_indexed 2023-09-18T22:22:29Z
last_indexed 2023-09-18T22:22:29Z
_version_ 1777415749302747136

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