[1]SHI Zhong-zhi,YIN Chao,YE Shi wei.A CBR algorithm supporting time series data[J].CAAI Transactions on Intelligent Systems,2007,2(1):40-44.
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A CBR algorithm supporting time series data

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 1 Page number: 40-44 Column: 学术论文—人工智能基础 Public date: 2007-02-25
Title:
A CBR algorithm supporting time series data
Author(s):
SHI Zhong-zhi1;  YIN Chao1; 2; YE Shiwei2
1.Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China；
2. School of Information Science and Engineering Graduate University of Chinese Ac ademy of Sciences, Beijing 100039, China
Keywords:
casebased reasoning;  time series data;  similarity c omparison
CLC:
TP399
DOI:
-
Abstract:
This paper focuses on the retrieval algorithms of a special kind of CBR system i n which cases are composed of timeseries data. We introduced the classical alg o rithm used for processing similarity queries on time series data. This algorithm is based on the fact that DFT preserves the Euclidean distance in the time or f requency domain, and only the first few elements of the frequency sequence are s ignificant, so the retrieval process can only use these significant elements to compute similarity degree. However, this algorithm has several disadvantages lim iting its usage in CBR retrieval, so a new algorithm is presented for using batc h meth od to compute the similarity degree. It is based on the observation that the ori ginal problem can be transformed to a convolution problem, and the circular conv olution can be computed more efficiently using FFT. Theoretical analysis and exp eriment result prove that this algorithm is efficient and robust. The algorithm presented in this paper furnishes the CBR with the ability to process cases cons ist of timeseries data.
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