Multiresolution Motif Discovery in Time Series

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IV – Our algorithm – Properties Interactivity • Feed a tree-like structure with our motifs at different resolutions • This allows to navigate in the motif hierarchy structure Nuno Castro and Paulo Azevedo 04/30/2010
IV – Our algorithm – Properties Space-Saving (SS) • Proposed* to efficiently compute frequent elements in data streams • Monitor only m words • For each new word e • If e is already monitored, increment its count • If not, replace the least frequent monitored element by e, and increment it • Experimentally shown to guarantee very small errors, with known upper-bounds on the over-estimation errors Reference*** Nuno Castro and Paulo Azevedo 04/30/2010
Page 1 and 2: Tenth SIAM International Conference
Page 3 and 4: I - Motif Definition • Motifs, al
Page 5 and 6: III - Related work limitations •
Page 7 and 8: IV - Our algorithm • We propose a
Page 9 and 10: IV - Our algorithm - Problem defini
Page 11 and 12: IV - Our algorithm Problem definiti
Page 13 and 14: IV - Our algorithm Properties • M
Page 15: IV - Our algorithm - Properties Mul
Page 19 and 20: V - Experimental Analysis • Scala
Page 21 and 22: V - Experimental Analysis - Scalabi
Page 23 and 24: V - Experimental Analysis - Scalabi
Page 25 and 26: V - Experimental Analysis Experimen
Page 27 and 28: VI - Conclusions • We have introd
Page 29 and 30: Thank you for your attention! • C
Page 31: On similarity Nuno Castro and Paulo

Multiresolution Motif Discovery in Time Series

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