MILAR: Mining Indirect Least Association Rule Algorithm

Abdullah, Zailani and Pramana Gusman, Aggy and Herawan, Tutut and Mat Deris, Mustafa (2016) MILAR: Mining Indirect Least Association Rule Algorithm. Ar early version of this paper has been appeared in Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013) (pp. 159-166). Springer Singapore. Journal of Computer Science and Information Technology, 1 (1). pp. 60-70.


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One of the interesting and meaningful information that is hiding in transactional database is indirect association rule. It corresponds to the property of high dependencies between two items that are rarely occurred together but indirectly emerged via another items. Since indirect association rule is nontrivial information, it can implicitly give a new perspective of relationship which cannot be directly observed from the common rule. Therefore, we proposed an algorithm for Mining Indirect Least Association Rule (MILAR) from the real and benchmarked datasets. MILAR is embedded with our scalable least measure namely Critical Relative Support (CRS). The experimental results show that MILAR can generate the desired rules in term of least and indirect least association rules. In addition, the obtained results can also be used by the domain experts to do further analysis and finally reveal more interesting findings. Keywords: Data mining; Association rule; Indirect; Least; Algorithm.

Item Type: Article
Subjects: 0 Research > Ilmu Komputer > Data Mining dan KDD
0 Research > Ilmu Komputer > Sistem Informasi
0 Research > Ilmu Komputer > Teknologi Komputer
Divisions/ Fakultas/ Prodi: LPPM (Lembaga Penelitian dan Pengabdian Masyarakat) UPI "YPTK"
Depositing User: Administrator
Date Deposited: 13 Mar 2018 07:35
Last Modified: 13 Mar 2018 07:35

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