In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
We consider the problem of efficiently computing the skyline against the most recent N elements in a data stream seen so far. Specifically, we study the n-of-N skyline queries; th...
Xuemin Lin, Yidong Yuan, Wei Wang 0011, Hongjun Lu
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
Abstract-- Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficient processing of continuous skyline que...
Wenjie Zhang, Xuemin Lin, Ying Zhang, Wei Wang 001...