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  • 标题:Study on Visual Techniques of Potential Pattern Discovery for Time Series Data
  • 本地全文:下载
  • 作者:Dalin Xu ; Yingmei Wei
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:232
  • DOI:10.1051/matecconf/201823202049
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Sequential pattern mining is always a very important branch of time series data mining. The pattern mining with visual means can be used to extract the knowledge of time series data more intuitively. Based on the research content, this paper analyzes the sequence pattern mining methods in different aspects and their combination with visualization technology. We further discuss and summarize the advantages of different visualization methods in discovering the potential patterns in time series data. Different systems and models have their unique information to show the focus. Compared with the characteristics of the model, the development and evolution of visualization technology for the discovery of potential patterns of time series data can be summarized. Finally, this paper discusses its development trend and how to play a greater role in the era of big data.
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