In this paper we propose a model for relevance feedback. Our model combines evidence from user's relevance assessments with algorithms describing how words are used within do...
Abstract. We propose a novel probabilistic method, based on latent variable models, for unsupervised topographic visualisation of dynamically evolving, coherent textual information...
Our research aims at discovering useful knowledge from the large collection of satellite images of typhoons using data mining approaches. We first introduce the creation of the typ...
In the traditional setting, text categorization is formulated as a concept learning problem where each instance is a single isolated document. However, this perspective is not appr...
Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining application domains including multimedia, CAD, molecular biology or medica...