Similar Subsequence Retrieval from Two Time Series Data Using Homology Search

被引：0

作者：

Nishii, Takuma ^{[1
]}

Hiroyasu, Tomoyuki ^{[2
]}

Yoshimi, Masato ^{[3
]}

Miki, Mitsunori ^{[3
]}

Yokouchi, Hisatake ^{[2
]}

机构：

[1] Doshisha Univ, Grad Sch Engn, Kyoto, Japan

[2] Doshisha Univ, Dept Life & Med Sci, Kyoto, Japan

[3] Doshisha Univ, Dept Sci & Engn, Kyoto, Japan

来源：

IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2010) | 2010年

关键词：

Time Series Data; Smith-Waterman Algorithm; Homology Search; Similarity Search; Requantization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a method for extracting the most similar subsequences from two time series data by quantizing them and performing a homology search. The homology searches, such as BLAST and SW, are string search algorithms. Therefore, time series data should be quantized. SAX and EIAD were applied as quantization methods, and their effectiveness was examined by experiment. According to the experiments, time series data sets were classified into four types of time series data set, and we discuss the characteristics of SAX and EIAD.

引用

页数：6