基于滑动窗口的数据流中近期频繁项挖掘

Mining recent frequent items from a sliding window over data streams

提出了一种在单独数据流中挖掘近期频繁项的算法MRFI。该算法采用基于对时间敏感的滑动窗口的模式,保证了挖掘结果的时效性,并利用循环队列和二叉排序树实现了简单高效的数据存储和处理,该方法是一种近似算法,它可以消除历史数据对挖掘结果的影响。实验采用IBM数据发生器产生合成数据,证明了该算法的有效性。

A new algorithm is proposed to mining recent frequent items in single data stream,called MRFI.The proposed algorithm works under time-sensitive sliding windows,and guarantees the mining result is recent.We used circular queue and binary sort tree to store and process streaming data that is simple and efficient.The proposed method is an approximate algorithm,it can eliminate the influence of old data to mined result.Based on the IBM test data generator,the experimental results show the feasibility and effectiveness of the algorithm.