Mining Frequent Itemsets using Temporal Association Rule
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R. Agrawal; T. Imielinski; A. Swami: “Mining Association Rules Between Sets of Items in Large Databases",page 207-216,SIGMOD Conference 1993.
Jian Pei, Jiawei Han, Yiwen Yin and Running Mao R : “Mining Frequent Pattern without Candidate Generation”, Kluwer online Academy 2004.
Keshari Verma,O.P.Vyas, ''Efficient calendar based association rule'',SIGMOD record,Vol.34,No.3,Sept. 2005.
Bo Wu, Defu Zhang, Qihua Lan, Jiemin Zheng “An Efficient Frequent Patterns Mining Algorithm based on Apriori Algorithm and the FP-tree Stucture” pages 1099-1102, 2008,ISBN 978-0-7695-3407-7.
Claudio Bettini, X. Sean Wang R: “Time Granularies in databases, Data Mining, and Temporal reasoning 2000. pp 230, ISBN 3-540- 66997-3, Springer-Verlag, July 2000. 230 pages. Monograph.
Juan M .Ale , Gustavo H. Rossi R: “ An approach to discovering temporal association rules”, ACM SIGDD March 1, 2002.
Panagiotis Papapetrou,George Kollios,Stan Sclaroff Dimitrios Gunopulos [2005]“Discovering Frequent Arrangements of Temporal Intervals” Proceedings of the Fifth IEEE International Conference on Data Mining (ICDM ’05)
J. Pei, J. Han, H. Lu, S. Nishio, S. Tang, and D. Yang, '' H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases '', Proc. 2001 Int. Conf. on Data Mining (ICDM'01)}, San Jose, CA, Nov. 2001.
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