Towards a hierarchical framework for predicting the best answer in a question answering system

This research aims to develop a model for identifying predictive variables for the selection of the best quality answer in a question-answering (QA) system. It was found that accuracy, completeness and relevance are strong predictors of the quality of the answer.

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Bibliographic Details
Main Authors:	Chua, Alton Yeow Kuan, Goh, Dion Hoe-Lian, Ling, Zhiquan, Blooma, Mohan John
Other Authors:	Wee Kim Wee School of Communication and Information
Format:	Conference or Workshop Item
Language:	English
Published:	2009
Subjects:	DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Online Access:	https://hdl.handle.net/10356/79616 http://hdl.handle.net/10220/6115
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-79616
record_format	dspace
spelling	sg-ntu-dr.10356-796162020-03-07T12:15:48Z Towards a hierarchical framework for predicting the best answer in a question answering system Chua, Alton Yeow Kuan Goh, Dion Hoe-Lian Ling, Zhiquan Blooma, Mohan John Wee Kim Wee School of Communication and Information International Conference on Asian Digital Libraries (10th : 2007 : Vietnam) DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval This research aims to develop a model for identifying predictive variables for the selection of the best quality answer in a question-answering (QA) system. It was found that accuracy, completeness and relevance are strong predictors of the quality of the answer. Accepted version 2009-10-01T07:45:15Z 2019-12-06T13:29:27Z 2009-10-01T07:45:15Z 2019-12-06T13:29:27Z 2007 2007 Conference Paper Blooma, M. J., Chua, A. Y. K., Goh, D. H. L., & Ling, Z. (2007). Towards a hierarchical framework for predicting the best answer in a question answering system. International Conference on Asian Digital Libraries ICADL (10th:2007:Vietnam), Lecture Notes in Computer Science, 4822, 497-498. https://hdl.handle.net/10356/79616 http://hdl.handle.net/10220/6115 10.1007/978-3-540-77094-7_65 en The original publication is available at www.springerlink.com. 3 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
spellingShingle	DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Chua, Alton Yeow Kuan Goh, Dion Hoe-Lian Ling, Zhiquan Blooma, Mohan John Towards a hierarchical framework for predicting the best answer in a question answering system
description	This research aims to develop a model for identifying predictive variables for the selection of the best quality answer in a question-answering (QA) system. It was found that accuracy, completeness and relevance are strong predictors of the quality of the answer.
author2	Wee Kim Wee School of Communication and Information
author_facet	Wee Kim Wee School of Communication and Information Chua, Alton Yeow Kuan Goh, Dion Hoe-Lian Ling, Zhiquan Blooma, Mohan John
format	Conference or Workshop Item
author	Chua, Alton Yeow Kuan Goh, Dion Hoe-Lian Ling, Zhiquan Blooma, Mohan John
author_sort	Chua, Alton Yeow Kuan
title	Towards a hierarchical framework for predicting the best answer in a question answering system
title_short	Towards a hierarchical framework for predicting the best answer in a question answering system
title_full	Towards a hierarchical framework for predicting the best answer in a question answering system
title_fullStr	Towards a hierarchical framework for predicting the best answer in a question answering system
title_full_unstemmed	Towards a hierarchical framework for predicting the best answer in a question answering system
title_sort	towards a hierarchical framework for predicting the best answer in a question answering system
publishDate	2009
url	https://hdl.handle.net/10356/79616 http://hdl.handle.net/10220/6115
_version_	1681048378855653376

Towards a hierarchical framework for predicting the best answer in a question answering system

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