Online Evaluation of Patterns from Evolving Web Data Streams
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Approximating sliding windows by cyclic tree-like histograms for efficient range queries
Data & Knowledge Engineering
Mining frequent items in data stream using time fading model
Information Sciences: an International Journal
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Capturing characteristics of large data streams has received considerable attention. The constraints in space and time often restrict the data stream processing to only one pass. Furthermore, processing data streams over sliding windows makes the problem more difficult and challenging. In this paper, we address the problem of estimating -approximate frequency in data streams over sliding windows. We are the first who propose an efficient algorithm which can achieve O(1/) space requirement and only need O(1) running time to process each item in the data stream and to answer a query.