A New Segmentation Algorithm to Stock Time Series based on PIP Approach

摘要：

Stock time series segmentation is one of the fundamental components in stock time series data mining. And the segmentation is often used for the trend analysis. In this paper, a new stock time series segmentation algorithm is proposed based on PIP(Perceptually Important Point) approach. This proposed segmentation method contributes to containing both the important data points and the primitive trends like uptrend and downtrend, while most of the current algorithms only contain one aspect of that. The proposed segmentation algorithm is proved to be more efficient and effective in reserving the trends and less complexity than those combined split-andmerge piecewise linear approximation segmentation algorithms.

关键词： segmentation PIP algorithm data mining

作者: Jian Jiang Zhe Zhang Huaiqing Wang

作者单位: Department of Information Systems City University of Hong Kong Hong Kong SAR

会议类型: 国际会议

会议名称: 第三届IEEE无线通讯、网络技术暨移动计算国际会议

会议地点: 上海

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）