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TIDES—a new descriptor for time series oscillation behavior

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Abstract

Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses the problems of indexing, clustering, classification, summarization, and anomaly detection. There is a wide range of techniques to describe and compare time series, but they focus on series’ values. This paper concentrates on a new aspect—that of describing oscillation patterns. It presents a technique for time series similarity search, and multiple temporal scales, defining a descriptor that uses the angular coefficients from a linear segmentation of the curve that represents the evolution of the analyzed series. This technique is generalized to handle co-evolution, in which several phenomena vary at the same time. Preliminary experiments with real datasets showed that our approach correctly characterizes the oscillation of single time series, for multiple time scales, and is able to compute the similarity among sets of co-evolving series.

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Notes

  1. We use vs to stress that the vector uses symbolic representation.

  2. www.cs.ucr.edu/~eamonn/timeseriesdata/

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Acknowledgements

This work was partially funded by CPqD Foundation, CAPES, FAPESP, CNPq grants and CNPq projects WebMAPS and RPG. It is also being partially funded by the Microsoft Research-FAPESP Virtual institute, under the eFarms project. We thank Jeferson Lobato Fernandes for providing us with experimental data.

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Authors and Affiliations

  1. Institute of Computing, University of Campinas—CP6176, Campinas, São Paulo, 13084-851, Brazil

    Leonardo E. Mariote, Claudia Bauzer Medeiros, Ricardo da Silva Torres & Lucas M. Bueno

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  1. Leonardo E. Mariote
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  2. Claudia Bauzer Medeiros
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  3. Ricardo da Silva Torres
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  4. Lucas M. Bueno
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Correspondence to Claudia Bauzer Medeiros.

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Mariote, L.E., Medeiros, C.B., Torres, R.d.S. et al. TIDES—a new descriptor for time series oscillation behavior. Geoinformatica 15, 75–109 (2011). https://doi.org/10.1007/s10707-010-0112-5

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  • DOI: https://doi.org/10.1007/s10707-010-0112-5

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