The advent of social network sites in the last years seems to be a trend that will likely continue. What naive technology users may not realize is that the information they provide...
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...