While complete understanding of arbitrary input text remains in the future, it is currently possible to construct natural language processing systems that provide a partial unders...
Peggy M. Andersen, Philip J. Hayes, Steven P. Wein...
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
Automated text categorisation systems learn a generalised hypothesis from large numbers of labelled examples. However, in many domains labelled data is scarce and expensive to obta...
In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is...
We present a hybrid text understanding methodology for the resolution of textual ellipsis. It integrates language-independent conceptual criteria and language-dependent functional...