Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
As the amount of data being generated in biology has increased, a major challenge has been how to store and represent this data in a way that makes it easily accessible to researc...
Michael Backhaus, Janet Kelso, Joshua Bacher, Hein...
—Modern applications such as web knowledge base, network traffic monitoring and online social networks have made available an unprecedented amount of network data with rich type...
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...