Author:
Li Yu-Chiang,Yeh Jieh-Shan,Chang Chin-Chen
Publisher
Springer Berlin Heidelberg
Reference18 articles.
1. Agarwal, R.C., Aggarwal, C.C., Prasad, V.V.V.: A tree projection algorithm for generation of frequent itemsets. Journal of Parallel and Distributed Computing 61, 350–361 (2001)
2. Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proc. 1993 ACM SIGMOD Intl. Conf. on Management of Data, Washington, D.C., pp. 207–216 (1993)
3. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proc. 20th Intl. Conf. on Very Large Data Bases, Santiago, Chile, pp. 487–499 (1994)
4. Lecture Notes in Artificial Intelligence;B. Barber,2000
5. Barber, B., Hamilton, H.J.: Parametric algorithm for mining share frequent itemsets. Journal of Intelligent Information Systems 16, 277–293 (2001)
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