A hierarchical matching of time series(HMTS) algorithm is proposed in this paper. The trend information of the time series is extracted using EMD(empirical mode decomposition) at first, subsequently piecewise linear segmentation is used to represent the trend of the series and the segmental line information is translated into 0-1 character, which substantially reduces the computational amount when comparing to the raw data. Finally the reduced series along with the series’ details are matched. As a result, the algorithm significantly improves the efficiency and accuracy of the similarity search, and overcome the difficulties of the direct linear segmentation representation of the raw data. The experimental results illustrate the effectiveness of this algorithm.