Abstract

A metro map can tell a story, as well as provide good directions. Though human attention and comprehension can be overwhelmed by the data deluge, automatic methods can extract structured knowledge and provide maps of complex information landscapes to help people understand ideas, connections, and storylines. Properties of good maps are difficult to formalize; important characteristics include coherence of storylines, coverage of diverse and important topics, and relationships among pieces of information. These principles can be used to synthesize meaningful narratives from large datasets across multiple domains, including news stories, research papers, legal cases, and works of literature.

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