This paper describes a probabilistic answer selection framework for question answering. In contrast with previous work using individual resources such as ontologies and the Web to...
Web-based search engines such as Google and NorthernLight return documents that are relevant to a user query, not answers to user questions. We have developed an architecture that...
Dragomir R. Radev, Weiguo Fan, Hong Qi, Harris Wu,...
We introduce a probabilistic noisychannel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outp...
In TREC 2007, Language Computer Corporation explored how a new, semantically-rich framework for information retrieval could be used to boost the overall performance of the answer ...
Andrew Hickl, Kirk Roberts, Bryan Rink, Jeremy Ben...
Abstract. Question answering systems aim to meet users' information needs by returning exact answers in response to a question. Traditional open domain question answering syst...