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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kurosawa, T. Takama, Y. |
| Copyright Year | 2011 |
| Abstract | This paper proposes a visualization system for getting insight into future research activities from co-authorship networks. A bibliographic network such as a co-authorship network and a citation network is important information for researchers when doing a research survey. In particular, there are many requests on research survey that relate with researchers' future activities, such as identification of remarkable of researchers including growing researchers and supervisors. Although a citation network has received many attentions from researchers, it is not suitable for such surveys because it reflects researchers' past activities. Since collaboration of researchers is essential for researchers' activities, co-authorship network is suitable for predicting future activities. In order to get insights into future research activities by discriminating growing research areas from grown-up areas, the proposed visualization system provides the function for identifying research areas and that for identifying time variation of both network structure and keyword distribution. As a basis for getting insights into future research activities, this paper focuses on the task of discriminating growing researchers from supervisors. The effectiveness of the proposed system is evaluated through the detailed analysis of two participants' analyzing process of InfoVis 2004 Contest dataset. |
| Starting Page | 332 |
| Ending Page | 339 |
| File Size | 822207 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457713736 |
| DOI | 10.1109/WI-IAT.2011.96 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-08-22 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization exploratory data analysis Brightness Collaboration Data visualization Color graph visualization Educational institutions temporal trend information co-authorship networks System analysis and design interactive information visualization |
| Content Type | Text |
| Resource Type | Article |
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