Analysis of Users’ Behavior on Book Loan Log Based On Association Rule Mining

Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

Abstract:

This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, Apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: Behavior, data mining technique, Apriori algorithm.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1336364

References:

[1] W. Frawley, G. Piatetsky-Shapiro, and C. Matheus, "Knowledge Discovery in Databases: An Overview”. AI Magazine, Fall 1992, pp. 213-228.
[2] R. Agrawal, T. Imielinski, and A.N. Swami, A. N., "Mining association rules between sets of items in large databases”, In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207-216,1993.
[3] Z. Qiankun, "Association Rule Mining: A Survey, Technical Report”, CAIS, Nanyang Technological University, Singapore , 2003
[4] R. Agrawal, and R. Srikant, "Fast algorithms for mining association rules”, In Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp. 487-499, 1994.
[5] http://www.cs.waikato.ac.nz/ml/weka/
[6] U. M. Fayyad, G. Pitatesky-Shapiro, P. Smyth, and R. Uthurasamy, "Advances in Knowledge Discovery and Data Mining”, AAAI/MIT Press, 1996.