: Conventional discussion environments provide the technical platform for distributed discussion and collaboration, but apart from some statistical data collected, rarely provide i...
Neural-symbolic integration concerns the integration of symbolic and connectionist systems. Distributed knowledge representation is traditionally seen under a purely symbolic pers...
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
In the same way that the Web has evolved from being a technology designed to aid scientific collaboration to one which is employed extensively in e-business and increasingly in e-...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...