Abstract
Data structures and relations are becoming increasingly complex and difficult to assess and manage. Although automated rules and algorithms can be used for many data-mining tasks, there are still situations where human attention and insight is required to identify unexpected circumstances or unanticipated patterns. Presentation of large quantities of data has always been a challenging task. In this paper a method for representing large graph-based data sets is proposed to help users navigate through large clusters of data. The proposed method is based on a stereoscopic 3D visualization with special enhancements for a large multi node graph visualization. The stereoscopic projection allows for utilization of techniques that can draw users’ attention to particular regions of the graph. The method uses specially established node-node relations to calculate attention drawing factor values for each graph node.
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Turek, M., Pałka, D., Zachara, M. (2017). Stereoscopic 3D Graph Visualization for Assisted Data Exploration and Discovery. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Network Information Systems. Advances in Intelligent Systems and Computing, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-43982-2_20
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DOI: https://doi.org/10.1007/978-3-319-43982-2_20
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