research-article

Towards faster and better retrieval models for question search

Authors:

Jun ZhaoAuthors Info & Claims

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Pages 2139 - 2148

https://doi.org/10.1145/2505515.2505550

Published: 27 October 2013 Publication History

Abstract

Community question answering (cQA) has become an important service due to the popularity of cQA archives on the web. This paper is concerned with the problem of question search. Question search in cQA aims to find the historical questions that are semantically equivalent or similar to the queried questions. In this paper, we propose a faster and better retrieval model for question search by leveraging user chosen category. After introducing the question category, we can filter certain amount of irrelevant historical questions under a wide range of leaf categories. Experimental results conducted on real cQA data set demonstrate that the proposed techniques are more effective and efficient than a variety of baseline methods.

References

[1]

D. Bernhard and I. Gurevych. 2009. Combining lexical semantic resources with question & answer archives for translation-based answer finding. In ACL, pages 728--736.

Digital Library

[2]

J. Bian, Y. Liu, E. Agichtein, and H. Zha. 2008. Finding the right facts in the crowd: factoid question answering over social media. In WWW, pages 467--476.

Digital Library

[3]

D. Blei, A. Ng, and M. Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993--1022.

Digital Library

[4]

R. Bunescu and Y. Huang. 2010. Learning the relative usefulness of questions in community QA. In EMNLP.

Digital Library

[5]

L. Cao, G. Zhou, K. Liu, and J. Zhao. 2011. Learning the latent topics for question retrieval in community QA. In IJCNLP.

[6]

X. Cao, G. Cong, B. Cui, C. Jensen, and C. Zhang. 2009. The use of categorization information in language models for question retrieval. In CIKM, pages 265--274.

Digital Library

[7]

X. Cao, G. Cong, B. Cui, and C. Jensen. 2010. A generalized framework of exploring category information for question retrieval in community question answer archives. In WWW.

Digital Library

[8]

A. P. Dempster, N. M. Laird, D. B. Rubin. 1977. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society. Series B (Methodological), 39(1):1--38.

[9]

H. Duan, Y. Cao, C. Lin, and Y. Yu. 2008. Searching questions by identifying questions topics and question focus. In ACL, pages 156--164.

[10]

T. Griffiths and M. Steyvers. 2004. Finding scientific topics. The National Academy of Sciences, 101:5228--5235.

[11]

J. Jeon, W. Croft, and J. Lee. 2005. Finding similar questions in large question and answer archives. In CIKM, pages 84--90.

Digital Library

[12]

S. Kullback and R. A. Leibler. 1951. On information and sufficiency. Annals of Mathematical Statistics 22 (1): 79--86.

[13]

J. Lee, S. Kim, Y. Song, and H. Rim. 2008. Bridging lexical gaps between queries and questions on large online Q&A collections with compact translation models. In EMNLP.

Digital Library

[14]

B. Li, I. King, and M. Lyu. 2011. Question routing in community question answering: putting category in its place. In CIKM.

Digital Library

[15]

C. Manning, P. Raghavan, and H. Schtze. 2008. Introduction to information retrieval. Cambridge University Press, New York, NY, USA.

Digital Library

[16]

S. Robertson, S. Walker, S. Jones, M. Hancock-Beaulieu, and M. Gatford. 1994. Okapi at trec-3. In TREC, pages 109--126.

[17]

G. Salton, A. Wong, and C. S. Yang. 1975. A vector space model for automatic indexing. Communications of the ACM, 18(11):613--620.

Digital Library

[18]

Y. -I. Song, C. -Y. Lin, Y. Cao, and H. -C. Rim. 2008. Question utility: a novel static ranking of question search. In AAAI, pages 1231--1236.

Digital Library

[19]

M. Surdeanu, M. Ciaramita, and H. Zaragoza. 2008. Learning to rank answers on large online qa collections. In ACL, pages 719--727.

[20]

S. Riezler, A. Vasserman, I. Tsochantaridis, V. Mittal, and Y. Liu. 2007. Statistical machine translation for query expansion in answer retrieval. In ACL, pages 464--471.

[21]

A. Singh. 2012. Entity based q&a retrieval. In EMNLP-CoNLL, pages 1266--1277.

Digital Library

[22]

K. Wang, Z. Ming, and T-S. Chua. 2009. A syntactic tree matching approach to finding similar questions in community-based qa services. In SIGIR, pages 187--194.

Digital Library

[23]

X. Wang, X. Tu, D. Feng, and L. Zhang. 2009. Ranking community answers by modeling question-answer relationships via analogical reasoning. In SIGIR.

Digital Library

[24]

B. Wang, X. Wang, C. Sun, B. Liu, and L. Sun. 2010. Modeling semantic relevance for question-answer pairs in web social communities. In ACL, pages 1230--1238.

Digital Library

[25]

G. Xue, D. Xing, Q. Yang, and Y. Yu. 2008. Deep classification in large-scale text hierarchies. In SIGIR.

Digital Library

[26]

X. Xue, J. Jeon, and W. Croft. 2008. Retrieval models for question and answer archives. In SIGIR, pages 475--482.

Digital Library

[27]

C. Zhai and J. Lafferty. 2001. A study of smooth methods for language models applied to ad hoc information retrieval. In SIGIR, pages 334--342.

Digital Library

[28]

G. Zhou, L. Cai, J. Zhao, and K. Liu. 2011. Phrase-based translation model for question retrieval in community question answer archives. In ACL, pages 653--662.

Digital Library

[29]

G. Zhou, K. Liu, and J. Zhao. 2012. Exploiting bilingual translation for question retrieval in community-based question answering. In COLING, pages 3153--3170.

[30]

G. Zhou, F. Liu, Y. Liu, S. He, and J. Zhao. 2013. Statistical Machine Translation Improves Question Retrieval in Community Question Answering via Matrix Factorization. In ACL, pages 852--861.

Cited By

Ha TNguyen VNguyen KNguyen KThan Q(2021)Utilizing SBERT For Finding Similar Questions in Community Question Answering2021 13th International Conference on Knowledge and Systems Engineering (KSE)10.1109/KSE53942.2021.9648830(1-6)Online publication date: 10-Nov-2021
https://doi.org/10.1109/KSE53942.2021.9648830
Wang ZFan YGuo JYang LZhang RLan YCheng XJiang HWang XHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)Match²Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401143(559-568)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401143
Edirisooriya MMahakalanda IYapa T(2019)Generalised Framework for Automated Conversational Agent Design via QFD2019 Moratuwa Engineering Research Conference (MERCon)10.1109/MERCon.2019.8818945(297-302)Online publication date: Jul-2019
https://doi.org/10.1109/MERCon.2019.8818945
Show More Cited By

Index Terms

Towards faster and better retrieval models for question search
1. Information systems
  1. Information retrieval

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cover image ACM Conferences

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

October 2013

2612 pages

ISBN:9781450322638

DOI:10.1145/2505515

General Chairs:
Qi He
LinkedIn, USA
,
Arun Iyengar
IBM T.J. Watson Research Center, USA
,
Program Chairs:
Wolfgang Nejdl
L3S Research Center, Germany
,
Jian Pei
Simon Fraser University, Canada
,
Rajeev Rastogi
Amazon, India

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 27 October 2013

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CIKM'13: 22nd ACM International Conference on Information and Knowledge Management

October 27 - November 1, 2013

California, San Francisco, USA

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CIKM '13 Paper Acceptance Rate 143 of 848 submissions, 17%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Ha TNguyen VNguyen KNguyen KThan Q(2021)Utilizing SBERT For Finding Similar Questions in Community Question Answering2021 13th International Conference on Knowledge and Systems Engineering (KSE)10.1109/KSE53942.2021.9648830(1-6)Online publication date: 10-Nov-2021
https://doi.org/10.1109/KSE53942.2021.9648830
Wang ZFan YGuo JYang LZhang RLan YCheng XJiang HWang XHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)Match²Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401143(559-568)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401143
Edirisooriya MMahakalanda IYapa T(2019)Generalised Framework for Automated Conversational Agent Design via QFD2019 Moratuwa Engineering Research Conference (MERCon)10.1109/MERCon.2019.8818945(297-302)Online publication date: Jul-2019
https://doi.org/10.1109/MERCon.2019.8818945
Othman NFaiz RSmaïli K(2019)Manhattan Siamese LSTM for Question Retrieval in Community Question AnsweringOn the Move to Meaningful Internet Systems: OTM 2019 Conferences10.1007/978-3-030-33246-4_41(661-677)Online publication date: 11-Oct-2019
https://doi.org/10.1007/978-3-030-33246-4_41
Wang PJi LYan JDou DSilva NZhang YJin L(2018)Concept and Attention-Based CNN for Question Retrieval in Multi-View LearningACM Transactions on Intelligent Systems and Technology10.1145/31519579:4(1-24)Online publication date: 31-Jan-2018
https://dl.acm.org/doi/10.1145/3151957
Ghosh KBhowmick PGoyal PSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Using re-ranking to boost deep learning based community question retrievalProceedings of the International Conference on Web Intelligence10.1145/3106426.3106442(807-814)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106442
Wang PZhang YJi LYan JJin Lde Rijke MShokouhi MTomkins AZhang M(2017)Concept Embedded Convolutional Semantic Model for Question RetrievalProceedings of the Tenth ACM International Conference on Web Search and Data Mining10.1145/3018661.3018687(395-403)Online publication date: 2-Feb-2017
https://dl.acm.org/doi/10.1145/3018661.3018687
Zhou GHuang J(2017)Modeling and Learning Distributed Word Representation with Metadata for Question RetrievalIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.266562529:6(1226-1239)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1109/TKDE.2017.2665625
Yu MZhang HZhang YQiao YZhao ZHe Y(2016)News Abridgement Algorithm Based on Word Alignment and Syntactic ParsingChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data10.1007/978-3-319-47674-2_26(313-323)Online publication date: 10-Oct-2016
https://doi.org/10.1007/978-3-319-47674-2_26
Hoogeveen DVerspoor KBaldwin T(2015)CQADupStackProceedings of the 20th Australasian Document Computing Symposium10.1145/2838931.2838934(1-8)Online publication date: 8-Dec-2015
https://dl.acm.org/doi/10.1145/2838931.2838934

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