University of Konstanz
Graduiertenkolleg / PhD Program
Computer and Information Science

Colloquium of the Department and the PhD Program


Learning and exploiting statistical dependencies in networks


Prof. Dr. David Jensen, University of Massachusetts Amherst, USA
Amherst, USA

date & place

Wednesday, 25.04.2007, 16:15 h
Room C252


Networks are ubiquitous in computer science and everyday life. We live embedded in social and professional networks, we communicate through telecommunications and computer networks, and we represent information in documents connected by hyperlinks and bibliographic citations. This talk will outline the unifying ideas behind three lines of my recent work on analyzing networks: 1) methods for learning joint distributions of variables on networks; 2) methods for navigating networks; and 3) methods for indexing network structure.

All these methods share a common thread -- representing and exploiting autocorrelation. Autocorrelation is a common feature of many social networks. For example, two individuals are more likely to share similar occupations, political beliefs, or cultural backgrounds if they are neighbors. In this talk, I will show how methods for modeling, navigation, and indexing can be unified by this key concept.