We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...
Abstract. In this paper, we present a method for the automatic acquisition of semantic-based reformulations from natural language questions. Our goal is to find useful and generic ...
Answer patterns have been shown to improve the performance of open-domain factoid QA systems. Their use, however, requires either constructing the patterns manually or developing ...
One of the major challenges in TRECstyle question-answering (QA) is to overcome the mismatch in the lexical representations in the query space and document space. This is particul...