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M. Waldner ,  D. Steinböck ,  E. Gröller (2020)

Interactive exploration of large time-dependent bipartite graphs

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Journal of Computer Languages

Abstract

Bipartite graphs are typically visualized using linked lists or matrices, but these visualizations neither scale well nor do they convey temporal development. We present a new interactive exploration interface for large, time-dependent bipartite graphs. We use two clustering techniques to build a hierarchical aggregation supporting different exploration strategies. Aggregated nodes and edges are visualized as linked lists with nested time series. We demonstrate two use cases: finding advertising expenses of public authorities following similar temporal patterns and comparing author-keyword co-occurrences across time. Through a user study, we show that linked lists with hierarchical aggregation lead to more insights than without.

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Forschungsgruppe

Keywords

Information visualization; Bipartite graphs; Clustering; Time series data; Insight-based evaluation

DOI