Derczynski, L., Wang, J., Gaizauskas, R. orcid.org/0000-0002-3356-5126 et al. (1 more author) (2008) A data driven approach to query expansion in question answering. In: Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for Question Answering. Coling 2008: The 2nd workshop on Information Retrieval for Question Answering, 2008-08-24., Manchester, UK. ACL Anthology , pp. 34-41.
Abstract
Automated answering of natural language questions is an interesting and useful problem to solve. Question answering (QA) systems often perform information retrieval at an initial stage. Information retrieval (IR) performance, provided by engines such as Lucene, places a bound on overall system performance. For example, no answer bearing documents are retrieved at low ranks for almost 40% of questions.
In this paper, answer texts from previous QA evaluations held as part of the Text REtrieval Conferences (TREC) are paired with queries and analysed in an attempt to identify performance-enhancing words. These words are then used to evaluate the performance of a query expansion method.
Data driven extension words were found to help in over 70% of difficult questions. These words can be used to improve and evaluate query expansion methods. Simple blind relevance feedback (RF) was correctly predicted as unlikely to help overall performance, and an possible explanation is provided for its low value in IR for QA.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2008 ACL. Licensed under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported license (http://creativecommons.org/licenses/by-nc-sa/3.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Feb 2020 15:25 |
Last Modified: | 07 Feb 2020 15:25 |
Published Version: | https://www.aclweb.org/anthology/W08-1805/ |
Status: | Published |
Publisher: | ACL Anthology |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113896 |