Query expansion for exploratory search with subtopic discovery in Community Question Answering

Gao, L; Lu, Y; Zhang, Q; Yang, H; Hu, Y

Query expansion for exploratory search with subtopic discovery in Community Question Answering

Gao, L Lu, Y Zhang, Q Yang, H

Hu, Y

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Joint Conference on Neural Networks, 2016, 2016-October pp. 4715 - 4720
Issue Date:: 2016-10-31

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Field	Value	Language
dc.contributor.author	Gao, L	en_US
dc.contributor.author	Lu, Y	en_US
dc.contributor.author	Zhang, Q	en_US
dc.contributor.author	Yang, H https://orcid.org/0000-0002-4328-335X	en_US
dc.contributor.author	Hu, Y	en_US
dc.date.issued	2016-10-31	en_US
dc.identifier.citation	Proceedings of the International Joint Conference on Neural Networks, 2016, 2016-October pp. 4715 - 4720	en_US
dc.identifier.isbn	9781509006199	en_US
dc.identifier.uri	http://hdl.handle.net/10453/106103
dc.description.abstract	© 2016 IEEE. Exploratory search is cumbersome with today's search engines, where a user aims to better understand complex concepts. Query expansions techniques have been widely used in exploratory search. However, query expansions often recommend queries that differ from the user's search intentions due to different contexts. Yet, many of users' needs could be addressed by asking people via popular Community Question Answering (CQA) services. In this paper, we investigate query expansion techniques for exploratory search using the resources of CQA to discover the user's search intentions. Specifically, we denote the explicit intuition as the subtopic that supports the user's exploratory task. We propose the method CqaQuExp to mine the subtopics, which mainly contains three subtask: Question retrieval, where we extract the questions and corresponding answers from CQA; subtopic mining, where we discover the subtopics based on the extracted information; Candidate concepts discovery, where we select the candidate concepts from the discovered subtopics for query expansion. Experimental results on real-world data from Yahoo! Answers demonstrate the effectiveness of the proposed methods.	en_US
dc.relation.ispartof	Proceedings of the International Joint Conference on Neural Networks	en_US
dc.relation.isbasedon	10.1109/IJCNN.2016.7727819	en_US
dc.title	Query expansion for exploratory search with subtopic discovery in Community Question Answering	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2016-October	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2016-October	en_US

Abstract:

© 2016 IEEE. Exploratory search is cumbersome with today's search engines, where a user aims to better understand complex concepts. Query expansions techniques have been widely used in exploratory search. However, query expansions often recommend queries that differ from the user's search intentions due to different contexts. Yet, many of users' needs could be addressed by asking people via popular Community Question Answering (CQA) services. In this paper, we investigate query expansion techniques for exploratory search using the resources of CQA to discover the user's search intentions. Specifically, we denote the explicit intuition as the subtopic that supports the user's exploratory task. We propose the method CqaQuExp to mine the subtopics, which mainly contains three subtask: Question retrieval, where we extract the questions and corresponding answers from CQA; subtopic mining, where we discover the subtopics based on the extracted information; Candidate concepts discovery, where we select the candidate concepts from the discovered subtopics for query expansion. Experimental results on real-world data from Yahoo! Answers demonstrate the effectiveness of the proposed methods.

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http://hdl.handle.net/10453/106103