Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of t...
Abstract This paper investigates whether a machine can automatically learn the task of finding, within a large collection of candidate responses, the answers to questions. The lea...
Adam L. Berger, Rich Caruana, David Cohn, Dayne Fr...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
This paper describes the use of machine learning to improve the performance of natural language question answering systems. We present a model for improving story comprehension th...
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
Michael Wiegand, Jochen L. Leidner, Dietrich Klako...