Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
A key issue in artificial intelligence lies in finding the amount of input detail needed to do successful learning. Too much detail causes overhead and makes learning prone to ove...
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
This paper presents a retrospective data analysis on how 75 clinicians searched for and accessed biomedical literature from an online information retrieval system to answer six cl...
The purpose of text clustering in information retrieval is to discover groups of semantically related documents. Accurate and comprehensible cluster descriptions (labels) let the ...