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2007
ACM

Ranked Subsequence Matching in Time-Series Databases

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Ranked Subsequence Matching in Time-Series Databases
Existing work on similar sequence matching has focused on either whole matching or range subsequence matching. In this paper, we present novel methods for ranked subsequence matching under time warping, which finds top-k subsequences most similar to a query sequence from data sequences. To the best of our knowledge, this is the first and most sophisticated subsequence matching solution mentioned in the literature. Specifically, we first provide a new notion of the minimum-distance matching-window pair (MDMWP) and formally define the mdmwp-distance, a lower bound between a data subsequence and a query sequence. The mdmwp-distance can be computed prior to accessing the actual subsequence. Based on the mdmwp-distance, we then develop a ranked subsequence matching algorithm to prune unnecessary subsequence accesses. Next, to reduce random disk I/Os and bad buffer utilization, we develop a method of deferred group subsequence retrieval. We then derive another lower bound, the window-group ...
Wook-Shin Han, Jinsoo Lee, Yang-Sae Moon, Haifeng
Added 05 Dec 2009
Updated 05 Dec 2009
Type Conference
Year 2007
Where VLDB
Authors Wook-Shin Han, Jinsoo Lee, Yang-Sae Moon, Haifeng Jiang
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