Metro Maps of Information

When information is abundant, it becomes increasingly difficult to fit nuggets of knowledge into a single coherent picture. Complex stories spaghetti into branches, side stories, and intertwining narratives. In order to explore these stories, one needs a map to navigate unfamiliar territory. We have developed a methodology for creating structured summaries of information, which we call metro maps. Our algorithm generates a concise structured set of documents which maximizes coverage of salient pieces of information. Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures the evolution of a story. We first formalize characteristics of good maps and formulate their construction as an optimization problem. Then, we provide efficient methods with theoretical guarantees for generating maps. Finally, we integrate capabilities for supporting user interaction into the framework, allowing users to guide the formulation of the maps so as to better reflect their interests. Pilot user studies with a realworld dataset demonstrate that the method is able to produce maps which help users to acquire knowledge efficiently.