论文信息 - Discord Discovery in Streaming Time Series based on an Improved HOT SAX Algorithm

Discord Discovery in Streaming Time Series based on an Improved HOT SAX Algorithm

In this paper, we propose an improved variant of HOT SAX algorithm, called HS-Squeezer, for efficient discord detection in static time series. HS-Squeezer employs clustering rather than augmented trie to arrange two ordering heuristics in HOT SAX. Furthermore, we introduce HS-Squeezer-Stream, the application of HS-Squeezer in the framework for detecting local discords in streaming time series. The experimental results reveal that HS-Squeezer can detect the same quality discords as those detected by HOT SAX but with much shorter run time. Furthermore, HS-Squeezer-Stream demonstrates a fast response in handling time series streams with quality local discords detected.

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