2Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases [ C ]//Proceedings of the ACM SIGMOD Conference on Management of Data. Washington D. C. ,1993:207-216.
3Agrawal R, Srikant R. Fast algorithms for mining association rules [ C ]//Proceedings 20th Inter-national Conference on Very Large Data Bases. MorganKaufmann, 1994: 487 -499.
4Hipp J, Guntzer U, Nakhaeizadeh G. Algorithms for association rule mining: A general survey and comparison[ J ]. SIGKDD Explorations, 2000, 2( 1 ) :58-64.
5Savasere A, Omiecinski E, Navathe S. An efficient algorithm for mining association rules in large databases [ C ]// Proceedings of the 21st International Conference on Very large Database. Zurich Switzerland, 1995.
6Zaki M J. Fast vertical Mining Using Diffsets[ R]. Technical Report 01-1, Rensselaer Polytechnic Institute, Troy, New York, 2001.
7Han J, Pei J, Yin Y. Mining frequent patterns without candidate generation [ C ]// Proc. 2000 ACM-SIGMOD Int. Conf. Management of Data( SIGMOD' 00). Dalas, TX, May 2000.
8Park J S, Chen M S, Yu P S. An effective hash-based algorithm for mining association rules [ C ]//Proceedings of ACM SIGMOD International Conference on Management of Data. San Jose, CA, 1995:175-186.
9Toivonen H. Sampling large databases for association rules [ C ]//Proceedings of the 22nd International Conference on Very Large Database. Bombay, India, 1996.
10Brin S, Motwani R, U11man J D, et al. Dynamic itemset counting and implication rules for market basket data [C]//Preoceedings of the 1997 ACM SIGMOD International Conference on Management of Data. volume 26 (2) of SIGMOD Record ,ACM Press,1997 : 255-264.
