FCA-ARMM: A Model for Mining Association Rules from Formal Concept Analysis

Author:

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

Publisher

Springer International Publishing

Reference22 articles.

1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings of 20th International Conference Very Large Data Bases (VLDB), vol. 1215, pp. 487–499. VLDB Endowment (1994)

2. Abdullah, Z., Herawan, T., Deris, M.M.: An alternative measure for mining weighted least association rule and its framework. In: Zain, J.M., et al. (eds.) ICSECS 2011, vol. 188, pp. 475–485. Springer, Heidelberg (2011). Part II

3. Abdullah, Z., Herawan, T., Ahmad, N., Deris, M.M.: Mining significant association rules from educational data using critical relative support approach. Procedia Soc. Behav. Sci. 28, 97–101 (2011). Science Direct

4. Abdullah, Z., Herawan, T., Deris, M.M.: Detecting definite least association rule in medical database. In: Herawan, T., Deris, M.M., Abawajy, J. (eds.) DaEng-2013. LNEE, vol. 285, pp. 127–134. Springer, Heidelberg (2014)

5. Poelmans, J., Elzinga, P., Viaene, S., Dedene, G.: Formal concept analysis in knowledge discovery: a survey. In: Croitoru, M., Ferré, S., Lukose, D. (eds.) ICCS-ConceptStruct 2010. LNCS, vol. 6208, pp. 139–153. Springer, Heidelberg (2010). 10.1007/978-3-642-14197-3_15

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