Journal of System Simulation
Abstract
Abstract: Time series data is the important research object of data mining. The current visual analysis technology of time series data rarely conducts the cross-domain correlation. The development and evolution of statistical time series data in the spatio-temporal domain and the text theme data in the cognitive domain cannot be simulitaneously supervised in a unified view. The user's visual analysis process based on cross-domain time series data is abstracted and a visual analysis process model is proposed. A multi-view collaborative cross-domain correlation visual analysis tool is designed on the basis of the model. The case study of epidemic time series data and public opinion text data show that the method can well support users to supervise the development and evolution of the time series data in different domain at the same time, and quickly explore the characteristic information and temporal and spatial changes of the data.
Recommended Citation
Han, Beibei; Wei, Yingmei; Fang, Yujie; and Wan, Shanshan
(2022)
"Visual Analysis of Cross-domain Association of Time-series Data,"
Journal of System Simulation: Vol. 34:
Iss.
1, Article 6.
DOI: 10.16182/j.issn1004731x.joss.20-0659
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss1/6
First Page
53
Revised Date
2020-12-15
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-0659
Last Page
61
CLC
TP391.9
Recommended Citation
Han Beibei, Wei Yingmei, Fang Yujie, Wan Shanshan. Visual Analysis of Cross-domain Association of Time-series Data[J]. Journal of System Simulation, 2022, 34(1): 53-61.
DOI
10.16182/j.issn1004731x.joss.20-0659
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