Mining approximate motifs in time series

• Type: Article in International Scientific Journal
• Date: 2006

Authors

Ferreira, PG (Author) Other; Azevedo, PJ (Author) Other; Silva, CG (Author) Other; Brito, RMM (Author) Other

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 32 Citations

Scientific classification

CORDIS: Physical sciences > Computer science > Informatics

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-PH7

DOI: 10.1007/11893318_12

Abstract (EN): The problem of discovering previously unknown frequent patterns in time series, also called motifs, has been recently introduced. A motif is a subseries pattern that appears a significant number of times. Results demonstrate that motifs may provide valuable insights about the data and have a wide range of applications in data mining tasks. The main motivation for this study was the need to mine time series data from protein folding/unfolding simulations. We propose an algorithm that extracts approximate motifs, i.e. motifs that capture portions of time series with a similar and eventually symmetric behavior. Preliminary results on the analysis of protein unfolding data support this proposal as a valuable tool. A.dditional experiments demonstrate that the application of utility of our algorithm is not limited to this particular problem. Rather it can be an interesting tool to be applied in many real world problems.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13