The following presentation is on Friday 11am (16-dec) at the boardroom (SIT 124).
TITLE: From Graphs to Maps
ABSTRACT: Information visualization can be invaluable in making sense
out of large data sets. However, traditional graph visualization methods
often fail to capture the underlying structural information, clustering,
and neighborhoods. Our algorithm for visualizing graphs as maps
provides a way to overcome some of the shortcomings with the help of the
geographic map metaphor. While graphs, charts, and tables often require
considerable effort to comprehend, a map representation is more
intuitive, as most people are very familiar with maps and even enjoy
carefully examining maps. The effectiveness of the map representation
algorithm is illustrated with applications in recommendation systems for
TV shows, movies, books, and music.
Several interesting and challenging geometric and graph theoretic
problems underlie this approach of creating maps from graphs.
Specifically, recent progress on contact representations, rectilinear
cartograms, and maximum differential coloring will be discussed.
Department of Computer Science, University of Arizona
(currently at Wilhelm-Schickard-Institut für Informatik, Universität Tübingen)
Stephen Kobourov is an Associate Professor of Computer Science at the
University of Arizona. He completed a BS degree in Mathematics and
Computer Science at Dartmouth College in 1995, and a PhD in Computer
Science at Johns Hopkins University in 2000. He has also worked as a
Research Scientist at AT&T Research Labs, and spent a year at the
University of Botswana as a Fulbright Scholar. Currently he works at
Universität Tübingen in Germany as a Humboldt Fellow.