TREC9 QA-Track Notebook Paper, NIST, Gaithersburg MD, One Search Engine or Two for Question-Answering John Prager, Eric Brown IBM T.J. Watson Research Center Yorktown Heights, N.Y

First Page		Document Content
Date: 2001-02-20 14:58:10 Natural language processing Computational linguistics Question answering Document retrieval Search engine indexing Precision and recall Dragomir R. Radev Relevance Subject Information science Information retrieval Science		TREC9 QA-Track Notebook Paper, NIST, Gaithersburg MD, One Search Engine or Two for Question-Answering John Prager, Eric Brown IBM T.J. Watson Research Center Yorktown Heights, N.Y Add to Reading List Source URL: trec.nist.gov Download Document from Source Website File Size: 47,85 KB Share Document on Facebook

	Structural Normalisation Methods for Improving Best Answer Identification in Question Answering Communities Grégoire Burel, Paul Mulholland and Harith Alani Knowledge Media Institute, Open University, UK {g.burel, p.mu DocID: 1xVWO - View Document
	Theorem-Proving by Resolution as a Basis for Question-Answering Systems Cordell Green Stanford Research Institute Menlo Park, California DocID: 1xVHV - View Document
	The use of theorem-proving techniques in question-answering systems by C. C O R D E L L G R E E N and BERTRAM RAPHAEL Stanford Research Institute Menlo Park, California DocID: 1xUl1 - View Document
	11 Theorem-Proving by Resolution as a Basis for Question-Answering Systems Cordell Green Stanford Research Institute Menlo Park. California DocID: 1xUis - View Document
	Neural Machine Translation for Query Construction and Composition Tommaso Soru 1 Edgard Marx 1 Andr´e Valdestilhas 1 Diego Esteves 2 Diego Moussallem 1 Gustavo Publio 1 Abstract Research on question answering with know DocID: 1xU5z - View Document