Article

Retrieving answers from frequently asked questions pages on the web

Authors:

Valentin Jijkoun,

Maarten de RijkeAuthors Info & Claims

CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management

Pages 76 - 83

https://doi.org/10.1145/1099554.1099571

Published: 31 October 2005 Publication History

Abstract

We address the task of answering natural language questions by using the large number of Frequently Asked Questions (FAQ) pages available on the web. The task involves three steps: (1) fetching FAQ pages from the web; (2) automatic extraction of question/answer (Q/A) pairs from the collected pages; and (3) answering users' questions by retrieving appropriate Q/A pairs. We discuss our solutions for each of the three tasks, and give detailed evaluation results on a collected corpus of about 3.6Gb of text data (293K pages, 2.8M Q/A pairs), with real users' questions sampled from a web search engine log. Specifically, we propose simple but effective methods for Q/A extraction and investigate task-specific retrieval models for answering questions. Our best model finds answers for 36% of the test questions in the top 20 results. Our overall conclusion is that FAQ pages on the web provide an excellent resource for addressing real users' information needs in a highly focused manner.

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Cited By

Zhang JHe JZhou YSun XYu X(2023)HSM-QA: Question Answering System Based on Hierarchical Semantic MatchingIEEE Access10.1109/ACCESS.2023.329685011(77826-77839)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3296850
Rashid MJamour FHristidis VDemartini GZuccon GCulpepper JHuang ZTong H(2021)QuAXProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482289(1518-1527)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482289
Li JJi CYan GYou LChen J(2021)An Ensemble Net of Convolutional Auto-Encoder and Graph Auto-Encoder for Auto-DiagnosisIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2020.298433513:1(189-199)Online publication date: Mar-2021
https://doi.org/10.1109/TCDS.2020.2984335
Show More Cited By

Index Terms

Retrieving answers from frequently asked questions pages on the web
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval

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Published In

cover image ACM Conferences

CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management

October 2005

854 pages

ISBN:1595931406

DOI:10.1145/1099554

General Chair:
Otthein Herzog
University of Bremen, Germany
,
Program Chairs:
Hans-Jörg Schek
University for Health Sciences, Medical Informatics and Technology, Austria
,
Norbert Fuhr
University of Duisburg-Essen, Germany
,
Abdur Chowdhury
America Online, USA
,
Wilfried Teiken
IBM T.J. Watson Research Center, USA

Copyright © 2005 ACM.

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Published: 31 October 2005

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CIKM05

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CIKM05: Conference on Information and Knowledge Management

October 31 - November 5, 2005

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CIKM '05 Paper Acceptance Rate 77 of 425 submissions, 18%;

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

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Cited By

Zhang JHe JZhou YSun XYu X(2023)HSM-QA: Question Answering System Based on Hierarchical Semantic MatchingIEEE Access10.1109/ACCESS.2023.329685011(77826-77839)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3296850
Rashid MJamour FHristidis VDemartini GZuccon GCulpepper JHuang ZTong H(2021)QuAXProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482289(1518-1527)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482289
Li JJi CYan GYou LChen J(2021)An Ensemble Net of Convolutional Auto-Encoder and Graph Auto-Encoder for Auto-DiagnosisIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2020.298433513:1(189-199)Online publication date: Mar-2021
https://doi.org/10.1109/TCDS.2020.2984335
Khushhal SMajid AAbbas SNadeem MShah S(2020)Question retrieval using combined queries in community question answeringJournal of Intelligent Information Systems10.1007/s10844-020-00612-xOnline publication date: 24-Jul-2020
https://doi.org/10.1007/s10844-020-00612-x
Damani SNarahari KChatterjee AGupta MAgrawal P(2020)Optimized Transformer Models for FAQ AnsweringAdvances in Knowledge Discovery and Data Mining10.1007/978-3-030-47426-3_19(235-248)Online publication date: 6-May-2020
https://doi.org/10.1007/978-3-030-47426-3_19
Ben Abacha ADemner-Fushman D(2019)A question-entailment approach to question answeringBMC Bioinformatics10.1186/s12859-019-3119-420:1Online publication date: 22-Oct-2019
https://doi.org/10.1186/s12859-019-3119-4
Gupta SCarvalho VPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)FAQ Retrieval Using Attentive MatchingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331294(929-932)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331294
Yulianti EChen RScholer FCroft WSanderson M(2018)Document Summarization for Answering Non-Factoid QueriesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.275437330:1(15-28)Online publication date: 1-Jan-2018
https://doi.org/10.1109/TKDE.2017.2754373
Nguyen DNguyen DPham SUnger CNgonga Ngomo ACimiano PAuer SPaliouras G(2017)Ripple Down Rules for question answeringSemantic Web10.3233/SW-1502048:4(511-532)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/SW-150204
Efraim OMaraev VRodrigues J(2017)Boosting a Rule-Based Chatbot Using Statistics and User Satisfaction RatingsArtificial Intelligence and Natural Language10.1007/978-3-319-71746-3_3(27-41)Online publication date: 28-Nov-2017
https://doi.org/10.1007/978-3-319-71746-3_3
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