By Topic

Time Series Discord Discovery Based on iSAX Symbolic Representation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

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