In this paper we present a novel, customizable IE paradigm that takes advantage of predicate-argument structures. We also introduce a new way of automatically identifying predicat...
Mihai Surdeanu, Sanda M. Harabagiu, John Williams,...
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Undiscovered relationships in a data set may confound analyses, particularly those that assume data independence. Such problems occur when characters used for phylogenetic analyse...
Anne M. Maglia, Jennifer L. Leopold, Venkat Ram Gh...
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...