In this paper we describe an approach to classifying objects in a domain where classifications are uncertain using a novel combination of argumentation and data mining. Classific...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...
Given a video and associated text, we propose an automatic annotation scheme in which we employ a latent topic model to generate topic distributions from weighted text and then mo...
Chris Engels, Koen Deschacht, Jan Hendrik Becker, ...
Background: Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate g...
This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm is designed for distributed inferencing, data compact...
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...