时间序列数据挖掘综述

Overview of time series data mining

在综合分析近年来时间序列数据挖掘相关文献的基础上,讨论了时间序列数据挖掘的最新进展,对各种学术观点进行了比较归类,并预测了其发展趋势。内容涵盖了时间序列数据变换、相似性搜索、预测、分类、聚类、分割、可视化等方面,为研究者了解最新的时间序列数据挖掘研究动态、新技术及发展趋势提供了参考。

Based on analyzing many literatures about time series data mining, this paper showed the development, academic opinions and proposed about time series data mining recently. The contents contained data transformation, similarity match, prediction, classification, clustering, segmentation and visualization of time series. The aim was to compare and classify these literatures and put forward reference for scholars who research development, new techniques and trends of time series data mining.