The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cada série temporal tem sua própria tendência linear, a direcionalidade de uma série temporal, e remover a tendência linear é crucial para obter resultados de correspondência mais intuitivos. Apoiar a redução da tendência linear no casamento de subsequências é um problema desafiador devido ao grande número de todas as subsequências possíveis. Neste artigo definimos esse problema como o correspondência de subsequência de redução de tendência linear e propor sua eficiência baseado em índice solução. Para isso, apresentamos primeiro uma noção de Janelas LD (LD significa eliminação de tendência linear). Usando as janelas LD, apresentamos então um teorema de limite inferior para a solução de correspondência baseada em índice e mostramos sua correção. A seguir propomos os algoritmos de construção de índice e correspondência de subsequências. Finalmente mostramos a superioridade da solução baseada em índices.
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Myeong-Seon GIL, Yang-Sae MOON, Bum-Soo KIM, "Linear Detrending Subsequence Matching in Time-Series Databases" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 4, pp. 917-920, April 2011, doi: 10.1587/transinf.E94.D.917.
Abstract: Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.917/_p
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@ARTICLE{e94-d_4_917,
author={Myeong-Seon GIL, Yang-Sae MOON, Bum-Soo KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Linear Detrending Subsequence Matching in Time-Series Databases},
year={2011},
volume={E94-D},
number={4},
pages={917-920},
abstract={Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.},
keywords={},
doi={10.1587/transinf.E94.D.917},
ISSN={1745-1361},
month={April},}
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TY - JOUR
TI - Linear Detrending Subsequence Matching in Time-Series Databases
T2 - IEICE TRANSACTIONS on Information
SP - 917
EP - 920
AU - Myeong-Seon GIL
AU - Yang-Sae MOON
AU - Bum-Soo KIM
PY - 2011
DO - 10.1587/transinf.E94.D.917
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2011
AB - Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.
ER -