Some Novel Heuristics for Finding the Most Unusual Time Series Subsequences

Thai Son Mai, Tuan Anh Duong

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

3 Citations (Scopus)


In this work, we introduce some novel heuristics which can enhance the efficiency of the Heuristic Discord Discovery (HDD) algorithm proposed by Keogh et al. for finding most unusual time series subsequences, called time series discords. Our new heuristics consist of a new discord measure function which helps to set up a range of alternative good orderings for the outer loop in the HDD algorithm and a branch-and-bound search mechanism that is carried out in the inner loop of the algorithm. Through extensive experiments on a variety of diverse datasets, our scheme is shown to have better performance than previous schemes, namely HOT SAX and WAT.
Original languageEnglish
Title of host publicationAdvances in Intelligent Information and Database Systems
Number of pages10
ISBN (Electronic)1860-9503
ISBN (Print)978-3-642-12089-3
Publication statusPublished - 2010
Externally publishedYes


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