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[1] R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules,” in Proc. of Int. Conf. on Very Large Data Bases, 1994. [2] J. Han, J. Pei, and Y. Yin, “Mining Frequent Patterns without Candidate Generation,” in Proc. of ACM-SIGMOD Int. Conf. on Management of Data, 2000. [3] J. Pei, J. Han, H. Lu, S. Nishio, S. Tang, and D. Yang, “H-Mine: Hyper-structure Mining of Frequent Patterns in Large Databases,” in Proc. of IEEE Int. Conf. on Data Mining (ICDM'01), 2001. [4] J. Han and J. Pei, “Pattern Growth Methods for Sequential Pattern Mining: Principles and Extensions,” in Proc. of ACM-SIGKDD Int. Conf. on Temporal Data Mining, 2001. [5] J. Pei, A.K.H. Tung, and J. Han, “Fault-Tolerant Frequent Pattern Mining: Problems and Challenges,” in Proc. of ACM-SIGMOD Int. Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD'01), 2001. [6] J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu, “PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth,” in Proc. Int. Conf. on Data Engineering (ICDE'01), 2001. [7] K. Wang, L. Tang, J. Han, J. Liu, “Top down FP-Growth for Association Rule Mining,” in Proc. of the 6th Pacific Area Conference on Knowledge Discovery and Data Mining (PAKDD-2002). [8] S.-S. Wang and S.-Y. Lee, “Mining Fault-Tolerant Frequent Patterns In Large Database,” in Proc. of Workshop on Software Engineering and Database Systems, International Computer Symposium, Taiwan, 2002. [9] M.-S. Chen, J. Han, P. Yu, “Data Mining: An Overview from Database Perspective,” IEEE Transactions on Knowledge and Data Engineering, 8(6): 866-883, 1996. [10] H. Pinto, J. Han, J. Pei, K. Wang, Q. Chen, and U. Dayal, “Multi-Dimensional Sequential Pattern Mining,” in Proc. of ACM Int. Conf. on Information and Knowledge Management, 2001. [11] M. Garofalakis, R. Rastogi, K. Shim, “SPIRIT: Sequential Pattern Mining with Regular Expression Constraints,” in Proc. of Int. Conf. on Very Large Data Bases, 1999. [12] M. J. Zaki, “Generating Non-Redundant Association Rules,” in Proc. of ACM-SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 2000. [13] J. Pei, J. Han, and R. Mao, “CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets,” in Proc. of ACM-SIGMOD Int. Workshop on Data Mining and Knowledge Discovery, 2000.
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