References: [1] Han, J., Kamber, M. (2006). Data Mining: Concepts and Techniques, Morgan Kaufmann in Elsevier, Second Edition, San Francisco. [2] Agrawal, R., Imielinksi, T., Swami, A. (1993). Database mining: a performance perspective, In: Proceedings of IEEE Transactions on Knowledge and Data, 5 (6) 914–925. [3] Saggar, M., Agrawal, A.K., Lad, A. (2004). Optimization of association rule mining using improved genetic algorithms, In.: Proceedings of the IEEE International Conference on Systems Man and Cybernetics, p. 3725– 3729. [4] Agrawal, R., Imielinski, T., Swami, A.N. (1993). Mining association rules between sets of items in large databases, In.: Proceedings of ACM SIGMOD international conference on Management of data, Washington, 22 (2) 207–216. [5] Houtsma, A., Swami, M. (1993). Set-oriented mining of association rules, Research Report RJ 9567, IBM Almaden Research Center, San Jose, California. [6] Birn, S., Motvani, R., D.Ullman, J., Tusr, S. (1997). Dynamic itemset counting and implication rules for market basket data, In: Proceedings of the ACM SIGMOD international conference on Management of data, New York, 26 (2) 255–264. [7] Khademolghorani, F. (2011). An effective algorithm for mining association rules based on Imperialist Competitive Algorithm, In: Proceedings of the sixth International Conference on Digital Information Management (ICDIM 2011), Melbourne, Austria, p. 6-11. [8] Kuo, R.J., Chao, C.M., Chiu, Y.T. (2009). Application of particle swarm optimization to association rule mining, Elsevier Applied Soft Computing, 11(1) 326-336. [9] Agrawal, R., Srikant, R. (1994). Fast algorithm for mining association rules in large databases, Research Report RJ 9839, IBM Almaden Research Center, San Francisco, CA, USA, p. 487-499. [10] Srikant, R., Agrawal, R. (1996). Mining quantitative association rules in large relational tables, In.: Proc. of ACM SIGMOD international conference on Management of data, Montreal, 25 (2) 1-12. [11] Mata, J., Alvarez, J., Riquelme, J. (2002). Discovering numeric association rules via evolutionary algorithm, In.: Proc of sixth Pacific–Asia conference on knowledge discovery and data mining PAKDD-02 (LNAI), Taiwan. p. 40-51. [12] Li, C., Yang, M. (2004). Association rule data mining in manufacturing information system based on genetic algorithms, In: Proceedings of the 3rd International Conference on Computational Electromagnetics and Its Applications, p. 153–156. [13] Kuo, R.J., Shih, C.W. (2007). Association rule mining through the ant colony system for National Health Insurance Research Database in Taiwan, Computers an Mathematics with Applications, Tarrytown, NY, USA, 54 (11-12) 1303–1318. [14] Kuo, R.J., Lin, S.Y., Shih, C.W. (2007). Discovering association rules through ant colony system for medical database in Taiwan, International Journal of Expert Systems with Applications, 33 (3) 794-808. [15] Ghosh, A., Nath, B. (2004). Multi-Objective Associa tion Rule Mining Using Genetic Algorithm, Elsevier Information Sciences, 163 (1) 123–133. [16] Badawy, O.M., Habib, M.I., Sallam, A.A. (2008). Quantitative Association Rule Mining Using a Hybrid PSO/ ACO Algorithm (PSO/ACO-AR), In: Proceedings of Arab Conference on Information Technology (ACIT’2008), Hammamet, Tunisia, p. 1-9. [17] Yan, X., Zhang, Ch., Zhang, Sh. (2009). Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support, processing of Expert Systems with Applications, 36 (2) 3066-3076 . [18] Qodmanan, H., Nasiri, M., Minaei-Bidgoli, B. (2010). Multi objective association rule mining with genetic algorithm without specifying minimum support and minimum confidence, In.: Proceedings of Elsevier Expert Systems with Applications, 38 (1) 288-298. [19] Nasiri, M., Taghavi, L., Minaei-Bidgoli, B. (2010). Multi-Objective Rule Mining using Simulated Annealing Algorithm, Soft Computing in Journal of Convergence Information Technology (JCDA), Korea, 5 (1) 60-68. [20] Khademolghorani, F., Baraani, A., Zamanifar, K. (2011). Efficient mining of association rules based on gravitational search algorithm, IJCSI International Journal of Computer Science Issues, Mahebourg, 8 (4) 1-8. [21] Atashpaz-Gargari, E., Lucas, C. (2007). Imperialist Competitive Algorithm An Algorithm for Optimization Inspired by Imperialistic Competition, IEEE Cogress on Evolutionary Compution, Singapore, p. 4661-4667. [22] Rose Tinabo. (2011). A Mechanism for Selecting Appropriate Data Mining Techniques, Journal of Intelligent Computing, 2 (1) 35-41. March. [23] Quanyin Zhu., Pei Zhou., Suqun Cao., Yunyang Yan., Jin Ding. (2012). A Novel RDB-SW Approach for Commodities Price Dynamic Trend Analysis Based on Web Mining, Journal of Digital Information Management, 10 (4) 168-173. August. [24] Yang Hang., Simon Fong. (2011). Algorithmic level stream mining for Business Intelligence System Architecture building, International Journal of Web Applications, 3 (1) 29-35. March, 2011. [25] Mohamed El Ghourabi., Amira Dridi., Fedya Telmoudi. (2011). Data Mining versus Statistical Tools for Value at Risk Estimation, Journal of Information Technology Review, 2 (4) 154-162. November, 2011. [26] Hassan I. Abdalla. (2011). New Technique to Deal with Dynamic Data Mining in the Database, Journal of Digital Information Management, 9 (4) 147-152. August 2011. |