One of the central challenges in sentimentbased text categorization is that not every portion of a document is equally informative for inferring the overall sentiment of the docum...
Most attempts to train part-of-speech taggers on a mixture of labeled and unlabeled data have failed. In this work stacked learning is used to reduce tagging to a classification t...
We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
Several methods for automatically generating labeled examples that can be used as training data for WSD systems have been proposed, including a semisupervised approach based on re...
Abstract. We present a tool developed for fostering probabilistic model checking of services formally specified in Scows, a stochastic enrichment of the Calculus for Orchestration ...