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Time Series Discord Discovery Based on iSAX Symbolic Representation

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2 Author(s)

Among several algorithms have been proposed to solve the problem of time series discord discovery, HOT SAX is one of the widely used algorithms. In this work, we employ state-of-the-art iSAX representation in time series discord discovery. We propose a new time series discord discovery algorithm, called HOTiSAX, by employing iSAX rather than SAX representation in discord discovery algorithm. The incorporation requires two new auxiliary functions to handle approximate non-self match search and exact non-self match search in the discord discovery algorithm. Besides, we devise a new heuristic to offer a better ordering for examining subsequences in the outer loop of HOTiSAX algorithm. We evaluate our algorithm with a set of experiments. Experimental results show that the new algorithm HOTiSAX outperforms the previous HOT SAX.

Published in:

Knowledge and Systems Engineering (KSE), 2011 Third International Conference on

Date of Conference:

14-17 Oct. 2011