A Hybrid Important Points Identification for Time Series: Financial Case
Important points identification is the key of the piecewise linear segmentation for time series. However, nearly all existing approaches are always perceptually important points (PIPs) focused while neglecting the domain related important points (DIPs) which might be of great interests to the domain experts. In order to preserve more important information relating to the particular domain after segmentation, a hybrid method to identify important points from both perceptual and domain perspectives is presented. We show the validity and effectiveness of the proposed method via a financial case.
time series piecewise linear segmentation perceptually important points domain important points fitting ef.fect
Yongwei Ding Xiaohu Yang Alexsander J. Kavs Juefeng Li
College of Computer Science and Technology Zhejiang University Hangzhou. P.R.China State Street Technology (Zhejiang) Hangzhou, P.R.China
国际会议
成都
英文
463-467
2010-06-23（万方平台首次上网日期，不代表论文的发表时间）