Experiencing SAX: a novel symbolic representation of time series
نویسندگان
چکیده
منابع مشابه
1d-SAX: A Novel Symbolic Representation for Time Series
SAX (Symbolic Aggregate approXimation) is one of the main symbolization technique for time series. A well-known limitation of SAX is that trends are not taken into account in the symbolization. This paper proposes 1d-SAX a method to represent a time series as a sequence of symbols that contain each an information about the average and the trend of the series on a segment. We compare the efficie...
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Efficient and accurate similarity searching for a large amount of time series data set is an important but non-trivial problem. Many dimensionality reduction techniques have been proposed for effective representation of time series data in order to realize such similarity searching, including Singular Value Decomposition (SVD), the Discrete Fourier transform (DFT), the Adaptive Piecewise Consta...
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The choice of an appropriate representation remains crucial for mining time series, particularly to reach a good trade-o between the dimensionality reduction and the stored information. Symbolic representations constitute a simple way of reducing the dimensionality by turning time series into sequences of symbols. SAXO is a data-driven symbolic representation of time series which encodes typica...
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Finding discords in time series database is an important problem in the last decade due to its variety of real-world applications, including data cleansing, fault diagnostics, and financial data analysis. The best known approach to our knowledge is HOT SAX technique based on the equiprobable distribution of SAX representations of time series. This characteristic, however, is not preserved in th...
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ژورنال
عنوان ژورنال: Data Mining and Knowledge Discovery
سال: 2007
ISSN: 1384-5810,1573-756X
DOI: 10.1007/s10618-007-0064-z