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Trains of Thought: Generating Information Maps

By Dafna Shahaf, Carlos Guestrin and Eric Horvitz


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 propose a methodology for creating structured summaries of information, which we call metro maps. Our proposed algorithm generates a concise structured set of documents maximizing coverage of salient pieces of information. Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures story development. 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 user interaction into our framework, allowing users to alter the maps to better reflect their interests. Pilot user studies with a real-world dataset demonstrate that the method is able to produce maps which help users acquire knowledge efficiently. Categories and Subject Descriptors Figure 1 shows a simplified metro map representing the H.3.1 [Information Storage and Retrieval]: Content debt crisis in Greece. The middle (blue) line details the Analysis and Indexing; H.3.3 [Information Storage and chain of events leading from Greece’s debt ‘junk ’ status to Retrieval]: Information Search and Retrieval; H.5 [Information the Greek bailout. The L-shaped (red) line is about strikes Interfaces and Presentation] and riots in Greece. Both lines intersect at an article about the austerity plan, since it plays an important role in both storylines: it was a key precondition fo

Year: 2012
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