References
- Ahn, K. and Kim, S. (2003). A new interestingness measure in association rules mining. Journal of the Korean Institute of Industrial Engineers, 29, 41-48.
- Berzal, F., Blanco, I., Sanchez, D. and Vila, M. (2001). A new framework to assess association rules. Proceedings of the 4th International Conference on Intelligent Data Analysis, 95-104.
- Hilderman, R. J. and Hamilton, H. J. (2000). Applying objective interestingness measures in data mining systems. Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery, 432-439.
- Hwang, J. and Kim, J. (2003). Target marketing using inverse association rule. Journal of Intelligence and Information Systems, 9, 195-209.
- Jin, D. S., Kang, C., Kim, K. K. and Choi, S. B. (2011). CRM on travel agency using association rules. Journal of the Korean Data Analysis Society, 13, 2945-2952.
- Kim, T. (2002). Estimation of defect rate from the screening test - The case of unknown sensitivity and specificity. Journal of the Korean Society for Quality Management, 30, 144-151.
- Kuo, Y. T. (2009) Mining surprising patterns, The doctoral paper of Melbourne university, Australia.
- Lavrac, N., Flach, P. and Zupan, B. (1999). Rule evaluation measures: a unifying view. Proceedings of the 9th International Workshop on Inductive Logic Programming, 174-185.
- Liu, B., Hsu, W., Chen, S. and Ma, Y. (2000). Analyzing the subjective interestingness of association rules. IEEE Intelligent Systems, 15, 47-55. https://doi.org/10.1109/5254.889106
- McNicholas, P.D., Murphy, T.B. and O'Regan, O. (2008). Standardising the lift of an association rule. Computational Statistics and Data Analysis, 52, 4712-4721. https://doi.org/10.1016/j.csda.2008.03.013
- Park, H. C. (2011a). The proposition of attributably pure confidence in association rule mining. Journal of the Korean Data & Information Science Society, 22, 235-243.
- Park, H. C. (2011b). Proposition of symmetrically pure confidence in association rule discovery. Journal of the Korean Data Analysis Society, 13, 879-890.
- Park, H. C. (2012). Exploration of symmetric similarity measures by conditional probabilities as association rule thresholds. Journal of the Korean Data Analysis Society, 14, 707-716.
- Park, H. C. (2013a). The proposition of c ompared and a ttributably pure confidence in association rule mining. Journal of the Korean Data & Information Science Society, 24, 523-532. https://doi.org/10.7465/jkdi.2013.24.3.523
- Park, H. C. (2013b). A proposition of association rule thresholds considering relative occurrence/ nonoccurrence. Journal of the Korean Data Analysis Society, 15, 1841-1850.
- Park, H. C. (2014a). Comparison of confidence measures useful for classification model building. Journal of the Korean Data & Information Science Society, 25, 365-371. https://doi.org/10.7465/jkdi.2014.25.2.365
- Park, H. C. (2014b). Proposition of causally confirmed measures in association rule mining. Journal of the Korean Data & Information Science Society, 25, 857-868. https://doi.org/10.7465/jkdi.2014.25.4.857
- Park, H. C. (2014c). Development of association rule threshold by balancing of relative rule accuracy. Journal of the Korean Data & Information Science Society, 25, 1345-1352. https://doi.org/10.7465/jkdi.2014.25.6.1345
- Piatetsky-Shapiro, G. (1991). Knowledge discovery in databases, MIT Press, Cambridge.
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