Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontol...
Few existing argumentation frameworks are designed to deal with probabilistic knowledge, and none are designed to represent possibilistic knowledge, making them unsuitable for man...
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...