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2018 | OriginalPaper | Buchkapitel

Interactive Temporal Visualization of Collaboration Networks

verfasst von : Ming Jing, Xueqing Li, Yupeng Hu

Erschienen in: Advances in Multimedia Information Processing – PCM 2017

Verlag: Springer International Publishing

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Abstract

Interactive visual analysis plays an important role to understand complex dataset. Literature data are most often visualized as collaboration networks to show the connection between researchers. However, the static networks barely transfer much information when the dataset including temporal variable. In this paper, we propose an embedded network visualization to display the temporal patterns hiding in the data and to avoid occlusion by intelligent filters. We research different graph style such as temporal display and direction to find the best way to present the temporal feature. Also, we demonstrate the usability of our approach with case studies on real bibliographic databases.

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Metadaten
Titel
Interactive Temporal Visualization of Collaboration Networks
verfasst von
Ming Jing
Xueqing Li
Yupeng Hu
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-77383-4_70

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