关键词: 时间序列, 相似性度量, 聚类, 数据挖掘

Abstract: In order to do the time-series similarity matching with the users’ needs and improve the accuracy, the time-series similarity matching based on event (SMBE) is proposed. First, the users’ needs are defined as the event and the original time series is translated into the event sequence. Then, SMBE is constructed. SMBE defines the similarity of the various elements in the two different sequences, constitute the corresponding similarity matrix and searches the optimal path value as the similarity measurement. Finally, the clustering method based on SMBE is proposed. Experimental results show that the clustering based on SMBE can get the accuracy of 90% with the reasonable parameters.

Key words: time series, similarity matching, clustering, data-mining