research-article

Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites

Authors:

Parikshit Sondhi,

ChengXiang ZhaiAuthors Info & Claims

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

Pages 341 - 350

https://doi.org/10.1145/2661829.2661968

Published: 03 November 2014 Publication History

Abstract

Over the past few years, community QA websites (e.g. Yahoo! Answers) have become a useful platform for users to post questions and obtain answers. However, not all questions posted there receive informative answers or are answered in a timely manner. In this paper, we show that the answers to some of these questions are available in online domain-specific knowledge bases and propose an approach to automatically discover those answers. In the proposed approach, we would first mine appropriate SQL query patterns by leveraging an existing collection of QA pairs, and then use the learned query patterns to answer previously unseen questions by returning relevant entities from the knowledge base. Evaluation on a collection of health domain questions from Yahoo! Answers shows that the proposed method is effective in discovering potential answers to user questions from an online medical knowledge base.

References

[1]

Trec question answering track. http://trec.nist.gov/data/qamain.html.

[2]

S. J. Athenikos and H. Han. Biomedical question answering: A survey. Computer Methods and Programs in Biomedicine, 99(1):1--24, 2010.

Digital Library

[3]

M. W. Bilotti, J. Elsas, J. Carbonell, and E. Nyberg. Rank learning for factoid question answering with linguistic and semantic constraints. In Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, pages 459--468, New York, NY, USA, 2010.

Digital Library

[4]

R. H. Byrd, J. Nocedal, and R. B. Schnabel. Representations of quasi-newton matrices and their use in limited memory methods. Math. Program., 63(2):129--156, Jan. 1994.

Digital Library

[5]

H. Cui, M.-Y. Kan, and T.-S. Chua. Generic soft pattern models for definitional question answering. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '05, pages 384--391, New York, NY, USA, 2005.

Digital Library

[6]

Z. Huang, M. Thint, and A. Celikyilmaz. Investigation of question classifier in question answering. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2, EMNLP '09, pages 543--550, Stroudsburg, PA, USA, 2009. Association for Computational Linguistics.

Digital Library

[7]

J. Jeon, W. B. Croft, and J. H. Lee. Finding similar questions in large question and answer archives. In Proceedings of the 14th ACM international conference on Information and knowledge management, CIKM '05, pages 84--90, New York, NY, USA, 2005.

Digital Library

[8]

V. Jijkoun and M. de Rijke. Retrieving answers from frequently asked questions pages on the web. In Proceedings of the 14th ACM international conference on Information and knowledge management, CIKM '05, pages 76--83, New York, NY, USA, 2005.

Digital Library

[9]

J. Kim, X. Xue, and W. B. Croft. A probabilistic retrieval model for semistructured data. In Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval, ECIR '09, pages 228--239, Berlin, Heidelberg, 2009. Springer-Verlag.

Digital Library

[10]

J. Y. Kim and W. B. Croft. A field relevance model for structured document retrieval. In Proceedings of the 34th European conference on Advances in Information Retrieval, ECIR'12, pages 97--108, Berlin, Heidelberg, 2012. Springer-Verlag.

Digital Library

[11]

M. Minock. C-phrase: A system for building robust natural language interfaces to databases. Data Knowl. Eng., 69(3):290--302, Mar. 2010.

Digital Library

[12]

A.-M. Popescu, A. Armanasu, O. Etzioni, D. Ko, and A. Yates. Modern natural language interfaces to databases: composing statistical parsing with semantic tractability. In Proceedings of the 20th international conference on Computational Linguistics, COLING '04, Stroudsburg, PA, USA, 2004. Association for Computational Linguistics.

Digital Library

[13]

S. Robertson, H. Zaragoza, and M. Taylor. Simple bm25 extension to multiple weighted fields. In Proceedings of the thirteenth ACM international conference on Information and knowledge management, CIKM '04, pages 42--49, New York, NY, USA, 2004.

Digital Library

[14]

R. Soricut and E. Brill. Automatic question answering using the web: Beyond the factoid. Inf. Retr., 9(2):191--206, Mar. 2006.

Digital Library

[15]

V. Tablan, D. Damljanovic, and K. Bontcheva. A natural language query interface to structured information. In Proceedings of the 5th European semantic web conference on The semantic web: research and applications, ESWC'08, pages 361--375, Berlin, Heidelberg, 2008. Springer-Verlag.

Digital Library

[16]

X. Xue, J. Jeon, and W. B. Croft. Retrieval models for question and answer archives. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '08, pages 475--482, New York, NY, USA, 2008.

Digital Library

[17]

C. Zhai. Statistical language models for information retrieval a critical review. Found. Trends Inf. Retr., 2(3):137--213, Mar. 2008.

Digital Library

[18]

C. Zhai and J. Lafferty. Model-based feedback in the language modeling approach to information retrieval. In Proceedings of the tenth international conference on Information and knowledge management, CIKM '01, pages 403--410, New York, NY, USA, 2001.

Digital Library

Cited By

Moulton MNg Y(2024)Boolean interpretation, matching, and ranking of natural language queries in product selection systemsDiscover Computing10.1007/s10791-024-09432-x27:1Online publication date: 3-Apr-2024
https://doi.org/10.1007/s10791-024-09432-x
Moulton MGao SNg Y(2022)Retrieving and Ranking Relevant Products from Boolean Natural Language Queries2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)10.1109/WI-IAT55865.2022.00051(303-308)Online publication date: Nov-2022
https://doi.org/10.1109/WI-IAT55865.2022.00051
Setia SIyengar SVerma ARobles GStol KWang X(2020)QWikiProceedings of the 16th International Symposium on Open Collaboration10.1145/3412569.3412576(1-12)Online publication date: 25-Aug-2020
https://dl.acm.org/doi/10.1145/3412569.3412576
Show More Cited By

Index Terms

Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

Recommendations

To Answer or Not to Answer? Filtering Questions for QA Systems
Intelligent Systems
Abstract
Question answering (QA) systems are usually structured as strict conditional generators, which return an answer for every input question. Sometimes, however, the policy of always responding to questions may prove itself harmful, given the ...
Using answer retrieval patterns to answer Portuguese questions
CLEF'08: Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access

Esfinge is a general domain Portuguese question answering system which has been participating at QA@CLEF since 2004. It uses the information available in the "official" document collections used in QA@CLEF (newspaper text and Wikipedia) and information ...
SPARQL-QA-v2 system for Knowledge Base Question Answering
Abstract
Accessing the large volumes of information available in public knowledge bases might be complicated for those users unfamiliar with formal languages, such as the SPARQL query language and the ontology definition languages. This issue ...
Highlights
- NMT-based approach resilient to out-of-vocabulary words for KBQA.
- Combination ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

November 2014

2152 pages

ISBN:9781450325981

DOI:10.1145/2661829

General Chairs:
Jianzhong Li
Harbin Inst. of Technology
,
X. Sean Wang
Fudan University
,
Program Chairs:
Minos Garofalakis
Technical University of Crete, Greece
,
Ian Soboroff
National Institute of Standards, USA
,
Torsten Suel
New York University, USA
,
Min Wang
Google Research, USA

Copyright © 2014 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Division of Computer and Network Systems

Conference

CIKM '14

Sponsor:

CIKM '14: 2014 ACM Conference on Information and Knowledge Management

November 3 - 7, 2014

Shanghai, China

Acceptance Rates

CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;

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

Upcoming Conference

CIKM '25

Sponsor:
sigir
sigir

The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
293
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)1

Reflects downloads up to 02 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Moulton MNg Y(2024)Boolean interpretation, matching, and ranking of natural language queries in product selection systemsDiscover Computing10.1007/s10791-024-09432-x27:1Online publication date: 3-Apr-2024
https://doi.org/10.1007/s10791-024-09432-x
Moulton MGao SNg Y(2022)Retrieving and Ranking Relevant Products from Boolean Natural Language Queries2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)10.1109/WI-IAT55865.2022.00051(303-308)Online publication date: Nov-2022
https://doi.org/10.1109/WI-IAT55865.2022.00051
Setia SIyengar SVerma ARobles GStol KWang X(2020)QWikiProceedings of the 16th International Symposium on Open Collaboration10.1145/3412569.3412576(1-12)Online publication date: 25-Aug-2020
https://dl.acm.org/doi/10.1145/3412569.3412576
Lima EShi WLiu XYu Q(2019)Integrating Multi-level Tag Recommendation with External Knowledge Bases for Automatic Question AnsweringACM Transactions on Internet Technology10.1145/331952819:3(1-22)Online publication date: 7-May-2019
https://dl.acm.org/doi/10.1145/3319528
Hoogeveen DWang LBaldwin TVerspoor K(2018)Web Forum Retrieval and Text AnalyticsFoundations and Trends in Information Retrieval10.1561/150000006212:1(1-163)Online publication date: 3-Jan-2018
https://dl.acm.org/doi/10.1561/1500000062
Xie HLu XTang ZChen JGonçalves MAllen JFox EKan MPetras V(2018)Clustering Analysis-Based Approach to Detecting Entity Mixture in Knowledge BasesProceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries10.1145/3197026.3203896(395-396)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3197026.3203896
Xie HLu XTang ZHuang X(2017)Detect Incorrect Triples in Knowledge Base Based on Triple Confidence EvaluationProceedings of the 3rd International Conference on Industrial and Business Engineering10.1145/3133811.3133829(93-101)Online publication date: 17-Aug-2017
https://dl.acm.org/doi/10.1145/3133811.3133829
Xie HLu XTang ZHuang X(2016)Detection of Entity Mixture in Knowledge Bases Using Hierarchical ClusteringNatural Language Understanding and Intelligent Applications10.1007/978-3-319-50496-4_24(288-299)Online publication date: 2-Dec-2016
https://doi.org/10.1007/978-3-319-50496-4_24
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

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten