Sliding window based weighted maximal frequent pattern mining over data streams
作者：
Highlights：
• We introduce a novel algorithm mining WMFPs with only one scan over sliding window-based data stream environment.
• We also provide a strategy which can prune unnecessary operations causing meaningless pattern generation in single paths.
• In performance evaluation, we show that our approach presents better performance than previous algorithms.
摘要
•We introduce a novel algorithm mining WMFPs with only one scan over sliding window-based data stream environment.•We also provide a strategy which can prune unnecessary operations causing meaningless pattern generation in single paths.•In performance evaluation, we show that our approach presents better performance than previous algorithms.
论文关键词：Data mining,Data stream,Sliding window,Weighted maximal frequent pattern mining
论文评审过程：Available online 14 August 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.094
