The exploration of large networks carries inherent challenges in the visualization of a great amount of data. We built an interactive visualization system for the purpose of exploring a large multidimensional network of news clips over time. These are clips gathered by users from web news sources and references to people or places are extracted from. In this paper, we present the system's capabilities and user interface and discuss its advantages in terms of the browsing and extraction of knowledge from the data. These capabilities include a textual search and associated event detection, and temporal navigation allowing the user to seek a certain date and timespan. © 2013 Springer-Verlag.
CITATION STYLE
Gomes, F., Devezas, J., & Figueira, Á. (2013). Temporal visualization of a multidimensional network of news clips. In Advances in Intelligent Systems and Computing (Vol. 206 AISC, pp. 157–166). Springer Verlag. https://doi.org/10.1007/978-3-642-36981-0_15
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