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2004

Question Answering Performance on Table Data

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Question Answering Performance on Table Data
Question answering (QA) on table data is a challenging information retrieval task. This paper describes a QA system for tables created with both machine learning and heuristic table extraction methods. Errors were analyzed in order to improve the system using government statistical data. We also apply these improvements on another type of table data set and show the experimental results.
Xing Wei, W. Bruce Croft, David Pinto
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Where DGO
Authors Xing Wei, W. Bruce Croft, David Pinto
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