We present a biology-inspired probabilistic graphical model, called the hypernetwork model, and its application to medical diagnosis of disease. The hypernetwork models are a way ...
JungWoo Ha, Jae-Hong Eom, Sung-Chun Kim, Byoung-Ta...
In this paper we propose a new approach to capture the inclination towards a certain election candidate from the contents of blogs and to explain why that inclination may be so. T...
In this paper, we define and study a novel text mining problem, which we refer to as Comparative Text Mining (CTM). Given a set of comparable text collections, the task of compara...
Background: Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is ...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...