# TOWARDS A FASTER SYMBOLIC AGGREGATE APPROXIMATION METHOD

### Muhammad Marwan Muhammad Fuad, Pierre-François Marteau

#### Abstract

The similarity search problem is one of the main problems in time series data mining. Traditionally, this problem was tackled by sequentially comparing the given query against all the time series in the database, and returning all the time series that are within a predetermined threshold of that query. But the large size and the high dimensionality of time series databases that are in use nowadays make that scenario inefficient. There are many representation techniques that aim at reducing the dimensionality of time series so that the search can be handled faster at a lower-dimensional space level. The symbolic aggregate approximation (SAX) is one of the most competitive methods in the literature. In this paper we present a new method that improves the performance of SAX by adding to it another exclusion condition that increases the exclusion power. This method is based on using two representations of the time series: one of SAX and the other is based on an optimal approximation of the time series. Pre-computed distances are calculated and stored offline to be used online to exclude a wide range of the search space using two exclusion conditions. We conduct experiments which show that the new method is faster than SAX.

#### References

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#### Paper Citation

#### in Harvard Style

Muhammad Fuad M. and Marteau P. (2010). **TOWARDS A FASTER SYMBOLIC AGGREGATE APPROXIMATION METHOD** . In *Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT,* ISBN 978-989-8425-22-5, pages 305-310. DOI: 10.5220/0003006703050310

#### in Bibtex Style

@conference{icsoft10,

author={Muhammad Marwan Muhammad Fuad and Pierre-François Marteau},

title={TOWARDS A FASTER SYMBOLIC AGGREGATE APPROXIMATION METHOD},

booktitle={Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT,},

year={2010},

pages={305-310},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0003006703050310},

isbn={978-989-8425-22-5},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT,

TI - TOWARDS A FASTER SYMBOLIC AGGREGATE APPROXIMATION METHOD

SN - 978-989-8425-22-5

AU - Muhammad Fuad M.

AU - Marteau P.

PY - 2010

SP - 305

EP - 310

DO - 10.5220/0003006703050310