Interactive visualization generation method for time series data based on transfer learning

被引：0
|
作者：
Zhou Z. [1 ]
Wang X. [2 ]
Chen W. [1 ,3 ]
机构：
[1] State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou
[2] College of Computer Science, Nankai University, Tianjin
[3] Laboratory of Art and Archaeology Image, Zhejiang University, Ministry of Education, Hangzhou
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2024年 / 58卷 / 02期
关键词：
interactive visualization generation; pattern recommendation; time series data visual analysis; transfer learning;
D O I：
10.3785/j.issn.1008-973X.2024.02.002
中图分类号：
学科分类号：
摘要：
An interactive visualization generation method for time series data based on transfer learning was proposed in order to address the inconsistency in data distribution across time-series data and facilitate the application of pattern analysis to other data. Transfer component analysis was applied to transfer features extracted from each time series data. The user’s analysis on one of the time series data served as labels. The classifier was trained on the source domain and applied to multiple target domains in order to achieve pattern recommendations. Two case studies and expert interviews with real-world weather data and bearing signal data were conducted to verify the effectiveness and practicality of the method by improving the efficiency of temporal data exploration and reducing the impact of inconsistent data distribution. © 2024 Zhejiang University. All rights reserved.
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页码：239 / 246
页数：7
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