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论文类型：期刊论文

发表时间：2011-12-01

发表刊物：Journal of Convergence Information Technology

收录刊物：EI、Scopus

卷号：6

期号：12

页面范围：163-170

ISSN号：19759320

摘要：Mining of time series pattern is an important research area, of which getting LCSS(Longest Common Subsequence) between high-dimensional time series is one of the most important issues. Large scale data needs to be handled in practical applications, so the research of efficient retrieval method is becoming a realistic work. Based on the issues above, we propose an efficient parallel algorithm to get LCSS between time series with the help of GPU (Graphics Processor Unit). On that basis, propose a parallel limit least matching rate LCSS algorithm (Parallel-Limited-LCSS), and optimize the retrieve parts of the algorithm with the help of inverted index structure, so as to enhance the efficiency of the algorithm. Experiments show that our algorithm has excellent speed and accuracy, and can be applied to the field of data mining widely.