Document summarization for answering non-factoid queries

Yulianti, E, Chen, R, Scholer, F, Croft, B and Sanderson, M 2018, 'Document summarization for answering non-factoid queries', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 1, pp. 15-28.


Document type: Journal Article
Collection: Journal Articles

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Title Document summarization for answering non-factoid queries
Author(s) Yulianti, E
Chen, R
Scholer, F
Croft, B
Sanderson, M
Year 2018
Journal name IEEE Transactions on Knowledge and Data Engineering
Volume number 30
Issue number 1
Start page 15
End page 28
Total pages 14
Publisher IEEE
Abstract We formulate a document summarization method to extract passage-level answers for non-factoid queries, referred as answer-biased summaries. We propose to use external information from related Community Question Answering (CQA) content to better identify answer bearing sentences. Three optimization-based methods are proposed: (i) query-biased; (ii) CQA-answer-biased; and (iii) expanded-query-biased, where expansion terms were derived from related CQA content. A learning-to-rank-based method is also proposed that incorporates features extracted from related CQA content. Our results show that even if a CQA answer does not contain a perfect answer to a query, their content can be exploited to improve the extraction of answer-biased summaries from other corpora. The quality of CQA content is found to impact on the accuracy of optimization-based summaries, though medium quality answers enable the system to achieve a comparable (and in some cases superior) accuracy to state-of-the-art techniques. The learning-to-rank-based summaries, on the other hand, are not significantly influenced by CQA quality. We provide a recommendation of the best use of our proposed approaches in regard to the availability of different quality levels of related CQA content. As a further investigation, the reliability of our approaches was tested on another publicly available dataset.
Subject Information Retrieval and Web Search
Keyword(s) answer-biased summaries
CQA
Data mining
document summarization
Feature extraction
Google
Knowledge discovery
learning-to-rank
non-factoid queries
Optimization
optimization
Search engines
Web search
DOI - identifier 10.1109/TKDE.2017.2754373
Copyright notice © 2017 IEEE
ISSN 1041-4347
Additional Notes Personal use is permitted, but republication/redistribution require IEEE permission.See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
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