Dynamic SAX parameter estimation for time series

Chaw Thet Zan*, Hayato Yamana

*この研究の対応する著者

    研究成果: Article査読

    6 被引用数 (Scopus)

    抄録

    Purpose - The paper aims to estimate the segment size and alphabet size of Symbolic Aggregate approXimation (SAX). In SAX, time series data are divided into a set of equal-sized segments. Each segment is represented by its mean value and mapped with an alphabet, where the number of adopted symbols is called alphabet size. Both parameters control data compression ratio and accuracy of time series mining tasks. Besides, optimal parameters selection highly depends on different application and data sets. In fact, these parameters are iteratively selected by analyzing entire data sets, which limits handling of the huge amount of time series and reduces the applicability of SAX. Design/methodology/approach - The segment size is estimated based on Shannon sampling theorem (autoSAXSD-S) and adaptive hierarchical segmentation (autoSAXSD-M). As for the alphabet size, it is focused on how mean values of all the segments are distributed. The small number of alphabet size is set for large distribution to easily distinguish the difference among segments. Findings - Experimental evaluation using University of California Riverside (UCR) data sets shows that the proposed schemes are able to select the parameters well with high classification accuracy and show comparable efficiency in comparison with state-of-the-art methods, SAX and auto-iSAX. Originality/value - The originality of this paper is the way to find out the optimal parameters of SAX using the proposed estimation schemes. The first parameter segment size is automatically estimated on two approaches and the second parameter alphabet size is estimated on the most frequent average (mean) value among segments.

    本文言語English
    ページ(範囲)387-404
    ページ数18
    ジャーナルInternational Journal of Web Information Systems
    13
    4
    DOI
    出版ステータスPublished - 2017 1月 1

    ASJC Scopus subject areas

    • 情報システム
    • コンピュータ ネットワークおよび通信

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