Author:
Rehman Zahoor ur,Shahbaz Muhammad,Shaheen Muhammad,Guergachi Aziz
Publisher
Springer Science and Business Media LLC
Reference45 articles.
1. Li, B.: Finding frequent itemsets from uncertain transaction streams. In: Proceedings of IEEE International Conference on Artificial Intelligence and Computational Intelligence, pp. 331–335, Shanghai, China (2009)
2. Yang B., Huang H.: TOPSIL-miner: an efficient algorithm for mining top-K significant itemsets over data streams. Knowl. Inf. Syst. 23, 225–242 (2009)
3. Chang, J.H.; Lee, W.S.: Finding recent frequent itemsets adaptively over online data streams. In: Proceedings of Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 487–492, New York, USA (2003)
4. Lee, D.; Lee, W.: Finding maximal frequent itemsets over online data streams adaptively. In: Proceedings of Fifth IEEE International Conference on Data Mining, pp. 266–273, Washington DC, USA (2005)
5. Manjhi, A.; Shkapenyuk, V.; Dhamdhere, K.; Olston, C.: Finding (recently) frequent items in distributed data streams. In: Proceedings of 21st International Conference on Data Engineering, pp. 767–778, Washington DC, USA (2005)
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献