Exploratory Analysis of Text Collections Through Visualization and Hybrid Biclustering

Nicolas Médoc (1, 2) , Mohammad Ghoniem (2) , Nadif Mohamed (1)

1 LIPADE - EA 2517 - Laboratoire d'Informatique Paris Descartes
2 LIST - Luxembourg Institute of Science and Technology

We propose a visual analytics tool to support analytic journalists in the exploration of large text corpora. Our tool combines graph modularity-based diagonal biclustering to extract high-level topics with overlapping bi-clustering to elicit fine-grained topic variants. A hybrid topic treemap visualization gives the analyst an overview of all topics. Coordinated sunburst and heatmap visualizations let the analyst inspect and compare topic variants and access document content on demand.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Nicolas Médoc, Mohammad Ghoniem, Nadif Mohamed. Exploratory Analysis of Text Collections Through Visualization and Hybrid Biclustering. Machine Learning and Knowledge Discovery in Databases, pp.59-62, 2016, Lecture Notes in Computer Science, 978-3-319-46130-4 978-3-319-46131-1. ⟨10.1007/978-3-319-46131-1_13⟩. ⟨hal-01390740⟩