We present a machine learning approach to evaluating the wellformedness of output of a machine translation system, using classifiers that learn to distinguish human reference tran...
Simon Corston-Oliver, Michael Gamon, Chris Brocket...
This paperpresents several industrial applications of MLin the context of their effort to solve the "KAMLproblem", i.e., the problem of merging knowledge acquisition and...
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
In this paper, we adapt a statistical learning approach, inspired by automated topic segmentation techniques in speech-recognized documents to the challenging protein segmentation ...
Betty Yee Man Cheng, Jaime G. Carbonell, Judith Kl...
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...