A Sliding Window Method for discovery of Recently Frequent Item sets over Online Data Streams
Ms.J.Gayathri
M.Sc., M.Phil., (Ph.D) Assistant Professor, Department of Computer Applications, KG College of Arts and Science, Coimbatore, , IN
Keywords: recently frequent itemsets, sliding window, data stream, mining data stream, change of data stream.
Abstract
A data stream is a massive unrestrained sequence of data elements continuously generated at a rapid rate.
Consequently, the knowledge entrenched in a data stream is likely to be changed as time goes by. However, most of
mining algorithms or frequency estimate algorithms for a data stream do not able to extract the recent change of
information in a data stream adaptively. This paper proposes a sliding window method of discovery of recently
frequent itemsets over an online data stream. The size of a window defines a favored life time of the information of a
transaction in a data stream.
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