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Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 786387, 12 pages
Discovery of Characteristic Patterns from Transactions with Their Classes
1Business Intelligence Laboratory and Advanced IT Laboratory, Toshiba Solutions Corporation, Tokyo 183-8512, Japan
2Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Kanagawa 226-8502, Japan
Received 21 October 2011; Revised 31 December 2011; Accepted 15 January 2012
Academic Editor: Tzung P. Hong
Copyright © 2012 Shigeaki Sakurai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- R. Agrawal and R. Srikant, “Fast algorithms for mining association rules in large databases,” in Proceedings of the 20th International Conferance on Very Large Data Bases, pp. 487–499, Santiago, Chile, 1994.
- T. Morzy and M. Zakrzewicz, “Group Bitmap Index: a structure for association rules retrieval,” in Proceedings of the International Conference on Knowledge Discovery and Data Mining, pp. 284–288, New York, NY, USA, 1998.
- M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li, “New algorithms for fast discovery of association rules,” in Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, pp. 283–286, Newport Beach, Calif, USA, 1997.
- J. Han, J. Pei, and Y. Yin, “Mining frequent patterns without candidate generation,” in Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 1–12, Dallas, Tex, USA, June 2000.
- Z. H. Deng and G. D. Fang, “Mining top-rank-K frequent patterns,” in Proceedings of the 6th International Conference on Machine Learning and Cybernetics (ICMLC '07), pp. 851–856, Hong Kong, August 2007.
- X. Yan, J. Han, and R. Afshar, “CloSpan: mining closed sequential patterns in large datasets,” in Proceedings of the SIAM International Conference on Data Mining, pp. 166–177, San Fransisco, Calif, USA, 2003.
- R. J. Bayardo Jr., “Efficiently mining long patterns from databases,” in Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 85–93, Seattle, Wash, USA, June 1998.
- C. H. Cai, A. W. C. Fu, C. H. Cheng, and W. W. Kwong, “Mining association rules with weighted items,” in Proceedings of the International Database Engineering and Applications Sympoium, pp. 68–77, Cardiff, UK, 1998.
- M. Pater and D. E. Popescu, “Multi-level database mining using AFOPT data structure and adaptive support constrains,” International Journal of Computers, Communications & Control, vol. 3, pp. 437–441, 2008.
- S. Sakurai and K. Mori, “Discovery of characteristic patterns from tabular structured data including missing values,” International Journal of Business Intelligence and Data Mining, vol. 5, no. 3, pp. 213–230, 2010.
- A. Ragel and B. Crémilleux, “Treatment of missing values for association rules,” in Proceedings of the 2nd Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining, pp. 258–270, Melbourne, Australia, 1998.
- T. Calders, B. Goethals, and M. Mampaey, “Mining itemsets in the presence of missing values,” in Proceedings of the ACM Symposium on Applied Computing, pp. 404–408, Seoul, Korea, March 2007.
- University of California Irvine, UCI Machine Learning Repository, 2011, http://archive.ics.uci.edu/ml/.
- S. Sakurai, “Prediction of sales volume based on the RFID data collected from apparel shops,” International Journal of Space-Based and Situated Computing, vol. 1, no. 2-3, pp. 174–182, 2011.