2013 Poster Sessions : Information Cartography: Creating Zoomable, Large-Scale Maps of Information

Student Name : Dafna Shahaf
Advisor : Jure Leskovec
Research Areas: Computer Systems
When information is abundant, users need support to understand complex stories, such as presidential elections or economical reforms. We propose a methodology for creating structured summaries of information, which we call zoomable metro maps. Just as cartographic maps have been relied upon for centuries to help us understand our surroundings, metro maps can help us understand the relationships between many pieces of information.

Given a large collection of news documents, our proposed algorithm generates a map of connections that explicitly capture story development. As different users might be interested in different granularities of the story, the maps are zoomable, with each level of zoom showing finer details and interactions. We formalize characteristics of good maps and formulate their construction as an optimization problem. We provide efficient, scalable methods with theoretical guarantees for generating maps. Pilot user studies over real-world datasets demonstrate that the method is able to produce maps which help users acquire knowledge efficiently.

Dafna Shahaf is a postdoctoral fellow at Stanford University, working with Prof. Jure Leskovec. She received her Ph.D. from Carnegie Mellon University; prior to that, she received her B.Sc. in mathematics and computer science from Tel-Aviv university, and her M.S. in computer science from the University of Illinois at Urbana-Champaign. Her research focuses on helping people make sense of large amounts of data by creating structured summaries of information. She has won a best research paper at KDD 2010, received Microsoft Research Fellowship, and is also a Siebel Scholar.