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Subsequence matching algorithm between number trend sequences
Jia Suling, Chen Dangyang,*
School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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Abstract�� To overcome the demerits of traditional trend sequences- analysis in temporal data mining, two concepts that were number trend sequences and trend sequences unwrapping were put forward. According to features of number trend sequences, radians were used to represent the trends of line segments. DTW-QS(dynamic time warping quick searching) algorithm was designed to solve the problem of subsequence matching between number trend sequences. The algorithm included three parts: DTW sequential searching, the mechanism of restriction and the mechanism of redundancy control, and DTW-QS algorithm was evaluated via experiments.
Keywords�� temporal data mining   trend sequence   subsequence matching     
Received 2006-04-08;


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Jia Suling, Chen Dangyang, .Subsequence matching algorithm between number trend sequences[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2007,V33(03): 350-353
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