Multiresolution Motif Discovery in Time Series
Multiresolution Motif Discovery in Time Series: MrMotif - ALFA
Multiresolution Motif Discovery in Time Series: MrMotif - ALFA
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IV – Our algorithm<br />
Problem def<strong>in</strong>ition<br />
• We follow a Top-K frequent pattern approach:<br />
• i.e. f<strong>in</strong>d<strong>in</strong>g the Top-K motifs<br />
• A time series can be counted as a repetition of another if<br />
they have the same symbolic representation<br />
• We use the Symbolic Aggregate Approximation (iSAX*)<br />
* Shieh, J. and Keogh, E., iSAX: <strong>in</strong>dex<strong>in</strong>g and m<strong>in</strong><strong>in</strong>g terabyte sized time series,<br />
<strong>in</strong> Proceed<strong>in</strong>gs of the 14th ACM SIGKDD <strong>in</strong>ternational Conference on Knowledge <strong>Discovery</strong> and Data M<strong>in</strong><strong>in</strong>g (2008), pp. 623-631.<br />
Nuno Castro and Paulo Azevedo<br />
04/30/2010