research-article

Variant search and syntactic tree similarity based approach to retrieve matching questions for SMS queries

Authors:

Akhil Langer,

Rohit Banga,

Ankush Mittal,

L. Venkata SubramaniamAuthors Info & Claims

AND '10: Proceedings of the fourth workshop on Analytics for noisy unstructured text data

Pages 67 - 72

https://doi.org/10.1145/1871840.1871851

Published: 26 October 2010 Publication History

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Abstract

Community based Question Answering archives have emerged as a very useful resource for instant access to comprehensive information in response to user queries. However, its access remains restricted to internet users. Access to this resource through Short Message Service (SMS) requires that a high precision automatic similar question matching system be built in order to decrease the search time by decreasing the number of SMS exchanges required. This paper proposes a solution that handles inherent noise in SMS queries through variant search, modeling the problem as one of combinatorial search. Following this, it uses syntactic tree matching to improve the ranking scheme. We present our analysis of the system and conduct experiments to test its feasibility. Experiments show that our approach outperforms the existing approaches significantly.

References

[1]

Apache lucene project. http://lucene.apache.org/.

Google Scholar

[2]

Extending google services in africa. http://googleblog.blogspot.com/2009/06/extendinggoogle-services-in-africa.html.

Google Scholar

[3]

R. D. Burke, K. J. Hammond, V. A. Kulyukin, S. L. Lytinen, N. Tomuro, and S. Schoenberg. Question answering from frequently asked question files: Experiences with the faq finder system. AI Magazine, 18(2):57--66, 1997.

Digital Library

Google Scholar

[4]

X. Cao, G. Cong, B. Cui, and C. Jensen. A generalized framework of exploring category information for question retrieval in community question answer archives. The 19th International World Wide Web Conference (WWW), pages 201--210, 2010.

Digital Library

Google Scholar

[5]

S. K. Kopparapu, A. Srivastava, and A. Pande. In proceedings of the 4th international conference on mobile technology, applications, and systems. In Proceedings of the 4th International conference on mobile technology, applications, and systems and the 1st International symposium on Computer human interaction in mobile technology, 2007.

Google Scholar

[6]

G. Kothari, S. Negi, T. A. Faruquie, V. T. Chakaravarthy, and L. V. Subramaniam. Sms based interface for faq retrieval. Proceedings: Joint Conference of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP), pages 852--860, Aug 2--7, 2009.

Digital Library

Google Scholar

[7]

K. Kukich. Technique for automatically correcting words in text. ACM Comput. Surv., 24(4):201--210, 1992.

Digital Library

Google Scholar

[8]

I. D. Melamed. Bitext maps and alignment via pattern recognition. Computational Linguistics, 1999.

Digital Library

Google Scholar

[9]

E. Prochasson, C. Viard-Gaudin, and E. Morin. Language models for handwritten short message services. In Proceedings of the 9th International Conference on Document Analysis and Recognition, 2007.

Digital Library

Google Scholar

[10]

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

Google Scholar

[11]

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

Digital Library

Google Scholar

[12]

D. Zhang and W. S. Lee. Question classification using support vector machines. In SIGIR 2003, pages 26--32, 2003.

Digital Library

Google Scholar

Cited By

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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
Langer ABanga RMittal ASubramaniam LSondhi P(2014)A text based drug query system for mobile phonesInternational Journal of Mobile Communications10.1504/IJMC.2014.06365612:4(411-429)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1504/IJMC.2014.063656
Adesina AAgbele KAbidoye ANyongesa H(2014)Text messaging and retrieval techniques for a mobile health information systemJournal of Information Science10.1177/016555151454040040:6(736-748)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1177/0165551514540400
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Index Terms

Variant search and syntactic tree similarity based approach to retrieve matching questions for SMS queries
1. Information systems
  1. Information retrieval

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Information & Contributors

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Published In

AND '10: Proceedings of the fourth workshop on Analytics for noisy unstructured text data

October 2010

96 pages

ISBN:9781450303767

DOI:10.1145/1871840

Program Chairs:
Roberto Basili
University of Rome, Italy
,
Daniel Lopresti
Lehigh University, USA
,
Christoph Ringlstetter
University of Munich, Germany
,
Shourya Roy
Xerox India Innovation Hub, India
,
Klaus U. Schulz
University of Munich, Germany
,
L. Venkata Subramaniam
IBM Research, India

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2010

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CIKM '10

Sponsor:

CIKM '10: International Conference on Information and Knowledge Management

October 26, 2010

ON, Toronto, Canada

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Overall Acceptance Rate 15 of 22 submissions, 68%

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Cited By

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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
Langer ABanga RMittal ASubramaniam LSondhi P(2014)A text based drug query system for mobile phonesInternational Journal of Mobile Communications10.1504/IJMC.2014.06365612:4(411-429)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1504/IJMC.2014.063656
Adesina AAgbele KAbidoye ANyongesa H(2014)Text messaging and retrieval techniques for a mobile health information systemJournal of Information Science10.1177/016555151454040040:6(736-748)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1177/0165551514540400
Batra RSharma SShrivastav AGoyal P(2014)Efficiently denoising SMS text for FAQ retrieval2014 International Conference on Data Mining and Intelligent Computing (ICDMIC)10.1109/ICDMIC.2014.6954237(1-5)Online publication date: Sep-2014
https://doi.org/10.1109/ICDMIC.2014.6954237
Jadhav SSomayajulu DBhattu SSubramanyam RSuresh P(2013)Context Dependent Bag of words generation2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)10.1109/ICACCI.2013.6637406(1526-1531)Online publication date: Aug-2013
https://doi.org/10.1109/ICACCI.2013.6637406
Banerjee UBora GBatra GAgarwal AGopalan KThampi S(2012)A novel software system to facilitate better and easier communication for people with speaking disabilitiesProceedings of the International Conference on Advances in Computing, Communications and Informatics10.1145/2345396.2345425(168-173)Online publication date: 3-Aug-2012
https://dl.acm.org/doi/10.1145/2345396.2345425

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A syntactic tree matching approach to finding similar questions in community-based qa services

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