We present Cluster Onset Detection (COD), a novel algorithm to aid in detection of epidemic outbreaks. COD employs unsupervised learning techniques in an online setting to partiti...
One of the objectives of this paper is to verify whether it is possible to extract meaningful related tags from a limited set of tagged resources and from resources tagged by only ...
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
This paper discusses the application of the Expectation-Maximization (EM) clustering algorithm to the task of Chinese verb sense discrimination. The model utilized rich linguistic...