A simpler and more efficient deterministic scheme for finding frequent items over sliding windows

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 the distribution of the item frequencies. It supports O(1/) update and query time, and uses O(1/) space. It is very simple; its main data structures are just a few short queues whose entries store the position of some items in the sliding window. We also extend our scheme for variable-size window. This extended scheme uses O(1/ log(n)) space. Categories and Subject Descriptors F.2 [Theory of Computation]: Analysis of Algorithms and Problem Complexity General Terms Algorithms, Theory Keywords Data Mining, Streaming Algorithms, Frequent Items, Network Monitoring

• Type: Conference
• Year: 2006
• Where: PODS
• Authors: Lap-Kei Lee, H. F. Ting
• Keywords: Approximate Frequent Items, Database, Extended Scheme, PODS 2006, Simple Scheme