FCA-ARMM

A model for mining association rules from formal concept analysis

Zailani Abdullah, Md Yazid Mohd Saman, Basyirah Karim, Tutut Herawan, Mustafa Mat Deris, Abdul Razak Hamdan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The evolution of technology in this era has contributed to a growing of abundant data. Data mining is a well-known computational process in discovering meaningful and useful information from large data repositories. There are various techniques in data mining that can be deal with this situation and one of them is association rule mining. Formal Concept Analysis (FCA) is a method of conceptual knowledge representation and data analysis. It has been applied in various disciplines including data mining. Extracting association rule from constructed FCA is very promising study but it is quite challenging, not straight forward and nearly unfocused. Therefore, in this paper we proposed an Integrated Formal Concept Analysis–Association Rule Mining Model (FCA-ARMM) and an open source tool called FCA-Miner. The results show that FCA-ARMM with FCA-Miner successful in generating the association rule from the real dataset.

Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings
PublisherSpringer Verlag
Pages213-223
Number of pages11
Volume549 AISC
ISBN (Print)9783319512792
DOIs
Publication statusPublished - 2017
EventThe 2nd International Conference on Soft Computing and Data Mining, SCDM-2016 - Bandung, Indonesia
Duration: 18 Aug 201620 Aug 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume549 AISC
ISSN (Print)21945357

Other

OtherThe 2nd International Conference on Soft Computing and Data Mining, SCDM-2016
CountryIndonesia
CityBandung
Period18/8/1620/8/16

Fingerprint

Formal concept analysis
Association rules
Data mining
Miners
Knowledge representation

Keywords

  • Association rule
  • Data mining
  • Formal concept analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Abdullah, Z., Saman, M. Y. M., Karim, B., Herawan, T., Deris, M. M., & Hamdan, A. R. (2017). FCA-ARMM: A model for mining association rules from formal concept analysis. In Recent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings (Vol. 549 AISC, pp. 213-223). (Advances in Intelligent Systems and Computing; Vol. 549 AISC). Springer Verlag. https://doi.org/10.1007/978-3-319-51281-5_22

FCA-ARMM : A model for mining association rules from formal concept analysis. / Abdullah, Zailani; Saman, Md Yazid Mohd; Karim, Basyirah; Herawan, Tutut; Deris, Mustafa Mat; Hamdan, Abdul Razak.

Recent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings. Vol. 549 AISC Springer Verlag, 2017. p. 213-223 (Advances in Intelligent Systems and Computing; Vol. 549 AISC).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abdullah, Z, Saman, MYM, Karim, B, Herawan, T, Deris, MM & Hamdan, AR 2017, FCA-ARMM: A model for mining association rules from formal concept analysis. in Recent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings. vol. 549 AISC, Advances in Intelligent Systems and Computing, vol. 549 AISC, Springer Verlag, pp. 213-223, The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Bandung, Indonesia, 18/8/16. https://doi.org/10.1007/978-3-319-51281-5_22
Abdullah Z, Saman MYM, Karim B, Herawan T, Deris MM, Hamdan AR. FCA-ARMM: A model for mining association rules from formal concept analysis. In Recent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings. Vol. 549 AISC. Springer Verlag. 2017. p. 213-223. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-51281-5_22
Abdullah, Zailani ; Saman, Md Yazid Mohd ; Karim, Basyirah ; Herawan, Tutut ; Deris, Mustafa Mat ; Hamdan, Abdul Razak. / FCA-ARMM : A model for mining association rules from formal concept analysis. Recent Advances on Soft Computing and Data Mining - The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016, Proceedings. Vol. 549 AISC Springer Verlag, 2017. pp. 213-223 (Advances in Intelligent Systems and Computing).
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