Mining frequent itemsets over tuple-evolving data streams
Proceedings of the 28th Annual ACM Symposium on Applied Computing (SAC '13)
By Carlo Zaniolo, Chongsheng Zhang, Florent Masseglia, Hamid Mousavi, Mirjana Mazuran, Yuan Hao
Issue Date:March 2013
In many data streaming applications today, tuples inside the streams may get revised over time. This type of data stream brings new issues and challenges to the data mining tasks. We present a theoretical analysis for mining frequent itemsets from sliding ...