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Finding Frequent Items in a Turnstile Data Stream

机译:在旋转栅数据流中查找频繁项

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摘要

Because of important applications such as denial-ofservice attack detection, finding frequent items in data streams under different models has been studied extensively. Finding frequent items in a turnstile data stream is the most challenging because both insertions and deletions of items are allowed in the stream. In this paper, we propose a deterministic algorithm that solves the problem. Furthermore, we propose a randomized algorithm for the problem. Empirical results show that our randomized algorithM provides better results than existing randomized algorithms for the problem and our algorithm uses much smaller space, and supports faster query time and similar update time.
机译:由于诸如拒绝服务攻击检测之类的重要应用,已经广泛研究了在不同模型下在数据流中查找频繁项的问题。在旋转式数据流中查找频繁项是最具挑战性的,因为在该流中允许插入和删除项。在本文中,我们提出了一种解决该问题的确定性算法。此外,我们针对该问题提出了一种随机算法。实验结果表明,与现有的随机算法相比,我们的随机算法提供了更好的结果,并且我们的算法使用更小的空间,并支持更快的查询时间和相似的​​更新时间。

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