Monday, November 7, 2011
Technische Universität Berlin
Institut für Mathematik
Straße des 17. Juni 136, 10623 Berlin
room MA 041
Lecture - 14:15
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.
Colloquium - 16:00
Abstract: