【摘要】 如何在线划分数据序列以满足持续动态增长的海量数据流需求正成为序列挖掘领域中的重要内容之一.本文提出一种新的基于层次聚类的在线序列分割算法(OSHC).利用数据序列的有序性特征,构造一种存储划分特征的链表结构 SF-List.该算法通过一次扫描数据库实现数据序列的在线划分,时间复杂度为 O(n).利用 SF-List中保存的划分特征信息,历史信息的快速查询成为可能.实验结果表明 OSHC 算法具有良好的划分性能和扩展性能.更多还原

【Abstract】 How to segment sequential data in real-time is becoming one of the most important tasks in the time series mining domain.A new online segmentation algorithm called online segmentation algorithm for time series based on hierarchical clustering(OSHC)is presented.According to the order characteristics of sequence data,a novel Segment Feature List(SF-List)is developed to save segmentation information.In the algorithm,time series are segmented effectively with one scan of the database and the time complexity is O(n).Historical information can also be inquired quickly by using the SF-List.Experimental results show that the algorithm is efficient.更多还原