We examine clarification dialogue, a mechanism for refining user questions with follow-up questions, in the context of open domain Question Answering systems. We develop an algori...
Creating more fine-grained annotated data than previously relevent document sets is important for evaluating individual components in automatic question answering systems. In this...
We present a machine learning approach for the task of ranking previously answered questions in a question repository with respect to their relevance to a new, unanswered referenc...
Information retrieval systems have typically concentrated on retrieving a set of documents which are relevant to a user's query. This paper describes a system that attempts t...
A central problem in Interactive Question Answering (IQA) is how to answer Follow-Up Questions (FU Qs), possibly by taking advantage of information from the dialogue context. We a...