2Agrawal R, Srikant R. Fast algorithms for mining association rules. In: Proc. of the 20th Int'l Conf. on VLDB. 1994. 487-499.http://www.almaden.ibm.conVcs/people/srikant/papers/vldb94.pdf.
3Bayardo R. Efficiently mining long patterns from databases. In: Haas LM, ed. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data. New York: ACM Press, 1998. 85-93.
4Burdick D, Calimlim M, Gehrke J. Mafia: A maximal frequent itemset algorithm for transactional databases. In: Proc. of the 17th Int'l Conf. on Data Engineering. 2001. 443-452. http://www.cs.cornell.edu/boom/2001 sp/yiu/mafia-camera.pdf.
5Gouda K, Zaki MJ. Efficiently mining maximal frequent itemsets. In: Proc. of the 1st IEEE Int'l Conf. on Data Mining. 2001.163-170. http ://www.cs .tau. ac .il/-fiat/dmsem03/E fficient%20Mining%20Maxmal%20Frequent%20Itemsets%20-%202001 .pdf.
6Wang H, Li QH. An improved maximal frequent itemset algorithm. In: Wang GY, eds. Proc of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, the 9th Int'l Conf (RSFDGrC 2003). LNCS 2639, Heidelberg: Springer-Verlag, 2003. 484-490.
7Zhou QH, Wesley C, Lu BJ. SmartMiner: A depth 1st algorithm guided by tail information for mining maximal frequent itemsets.In: Proc of the IEEE Int'l Conf on Data Mining (ICDM2002). 2002. 570-577. http://www.serviceware.com/pdffiles/datasheets/ServiceWare-Smartminer-Datasheet.pdf.
8Grahne G, Zhu JF. High performance mining of maximal frequent itemsets. In: Proc of the 6th SIAM Int'l Workshop on High Performance Data Mining (HPDM 2003). 2003. 135-143. http://www.cs.concordia.ca/db/dbdm/hpdm03.pdf.
9Agarwal RC, Aggarwal CC, Prasad VVV. Depth 1 st generation of long patterns. In: Proc. of the 6th ACM SIGKDD Int'l Conf on Knowledge Discovery and Data Mining. 2000. 108-118. http://www.cs.tau.ac.il/-fiat/dmsem03/Depth%20First%20Generation%20of%20Long%20Patterns%20-%202000.pdf.