Jan 27, 2012 · It exploits a compact data structure to maintain potentially frequent itemsets so that it can output recent frequent itemsets at any time.

Experiments compare the time and space usage with MFI-TransSW, which also returns all accurate frequent itemsets from sliding windows. The results show that BFI ...

Online mining of frequent itemsets over a stream sliding window is one of the most important problems in stream data mining with broad applications.

Online mining of frequent itemsets over a stream sliding window is one of the most important problems in stream data mining with broad applications.

Mining Recent Frequent Itemsets over Data Streams with a Time-Sensitive Sliding Window. Conference paper. pp 62–73; Cite this conference paper. Download book ...

In this paper, we proposed an one-pass data stream mining algorithm to mine the recent frequent itemsets in data streams with a sliding window basing on ...

This paper proposes a data mining method for finding recent frequent itemsets adaptively over an online data stream. The effect of old transactions on the ...

Mining frequent itemsets over data streams is an emergent research topic in recent years. In data streams, new data are continuously coming as time advances ...

This paper proposes a sliding window method that finds recently frequent itemsets over a transactional online data stream adaptively. The size of a sliding ...

Online mining of frequent itemsets over a stream sliding window is one of the most important problems in stream data mining with broad applications.