Visual Analysis of Cross-domain Association of Time-series Data

doi:10.16182/j.issn1004731x.joss.20-0659

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.

Key words: time series data, text theme data, spatio-temporal domain, cognitive domain, cross domain correlation, visual analytics

CLC Number:

TP391.9

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.

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