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Parameter-free search of time-series discord

Version 2 2024-06-03, 19:53
Version 1 2014-10-28, 10:10
journal contribution
posted on 2013-01-01, 00:00 authored by Wei LuoWei Luo, M Gallagher, J Wiles
Time-series discord is widely used in data mining applications to characterize anomalous subsequences in time series. Compared to some other discord search algorithms, the direct search algorithm based on the recurrence plot shows the advantage of being fast and parameter free. The direct search algorithm, however, relies on quasi-periodicity in input time series, an assumption that limits the algorithm's applicability. In this paper, we eliminate the periodicity assumption from the direct search algorithm by proposing a reference function for subsequences and a new sampling strategy based on the reference function. These measures result in a new algorithm with improved efficiency and robustness, as evidenced by our empirical evaluation.

History

Journal

Journal of computer science and technology

Volume

28

Issue

2

Pagination

300 - 310

Publisher

Springer

Location

Berlin, Germany

ISSN

1000-9000

eISSN

1860-4749

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2013, Springer