research-article

Dual role model for question recommendation in community question answering

Authors:

Bin WangAuthors Info & Claims

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Pages 771 - 780

https://doi.org/10.1145/2348283.2348387

Published: 12 August 2012 Publication History

Abstract

Question recommendation that automatically recommends a new question to suitable users to answer is an appealing and challenging problem in the research area of Community Question Answering (CQA). Unlike in general recommender systems where a user has only a single role, each user in CQA can play two different roles (dual roles) simultaneously: as an asker and as an answerer. To the best of our knowledge, this paper is the first to systematically investigate the distinctions between the two roles and their different influences on the performance of question recommendation in CQA. Moreover, we propose a Dual Role Model (DRM) to model the dual roles of users effectively. With different indepen-dence assumptions, two variants of DRM are achieved. Finally, we present the DRM based approach to question recommendation which provides a mechanism for naturally integrating the user relation between the answerer and the asker with the content re-levance between the answerer and the question into a uni-fied probabilistic framework. Experiments using a real-world data crawled from Yahoo! Answers show that: (1) there are evident distinctions between the two roles of users in CQA. Additionally, the answerer role is more effective than the asker role for modeling candidate users in question recommendation; (2) compared with baselines utilizing a single role or blended roles based methods, our DRM based approach consistently and significantly improves the performance of question recommendation, demonstrating that our approach can model the user in CQA more reasonably and precisely.

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Cited By

Andreasen TBordogna GTré GKacprzyk JLarsen HZadrożny S(2024)The power and potentials of Flexible Query Answering Systems: A critical and comprehensive analysisData & Knowledge Engineering10.1016/j.datak.2023.102246149(102246)Online publication date: Jan-2024
https://doi.org/10.1016/j.datak.2023.102246
Tang BGao QCui XPeng QYu X(2023)Feature-Alignment-Based Cross-Platform Question Answering Expert RecommendationMathematics10.3390/math1109217411:9(2174)Online publication date: 5-May-2023
https://doi.org/10.3390/math11092174
Kasela PPasi GPerego R(2023)SE-PEF: a Resource for Personalized Expert FindingProceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3624918.3625335(288-309)Online publication date: 26-Nov-2023
https://dl.acm.org/doi/10.1145/3624918.3625335
Show More Cited By

Index Terms

Dual role model for question recommendation in community question answering
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Abstract
In this paper, we address the problem of question recommendation that automatically recommends a new question to suitable users to answer in community question answering (CQA). The major challenge of question recommendation is the accurate ...

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Published In

cover image ACM Conferences

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

Copyright © 2012 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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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

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SIGIR '12

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SIGIR

SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Andreasen TBordogna GTré GKacprzyk JLarsen HZadrożny S(2024)The power and potentials of Flexible Query Answering Systems: A critical and comprehensive analysisData & Knowledge Engineering10.1016/j.datak.2023.102246149(102246)Online publication date: Jan-2024
https://doi.org/10.1016/j.datak.2023.102246
Tang BGao QCui XPeng QYu X(2023)Feature-Alignment-Based Cross-Platform Question Answering Expert RecommendationMathematics10.3390/math1109217411:9(2174)Online publication date: 5-May-2023
https://doi.org/10.3390/math11092174
Kasela PPasi GPerego R(2023)SE-PEF: a Resource for Personalized Expert FindingProceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3624918.3625335(288-309)Online publication date: 26-Nov-2023
https://dl.acm.org/doi/10.1145/3624918.3625335
Costa GOrtale R(2023) Ask and Ye shall be AnsweredInformation Fusion10.1016/j.inffus.2023.10185699:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.inffus.2023.101856
Costa GOrtale R(2023)Here are the answers. What is your question? Bayesian collaborative tag-based recommendation of time-sensitive expertise in question-answering communitiesExpert Systems with Applications10.1016/j.eswa.2023.120042225(120042)Online publication date: Sep-2023
https://doi.org/10.1016/j.eswa.2023.120042
Wang GCheng DXia DJiang H(2023)Swarm Intelligence Research: From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm IntelligenceMachine Intelligence Research10.1007/s11633-022-1367-720:1(121-144)Online publication date: 10-Jan-2023
https://doi.org/10.1007/s11633-022-1367-7
Li NGuo BLiu YDing YXu EYao LYu Z(2022)Transfer how much: a fine-grained measure of the knowledge transferability of user behavior sequences in social networkData Mining and Knowledge Discovery10.1007/s10618-022-00857-w36:6(2214-2236)Online publication date: 17-Sep-2022
https://doi.org/10.1007/s10618-022-00857-w
Guessoum MDjiroun RBoukhalfa KBenkhelifa E(2022)Natural language why-question in Business Intelligence applications: model and recommendation approachCluster Computing10.1007/s10586-022-03593-425:6(3875-3898)Online publication date: 18-May-2022
https://doi.org/10.1007/s10586-022-03593-4
Askari AVerberne SPasi G(2022)Expert Finding in Legal Community Question AnsweringAdvances in Information Retrieval10.1007/978-3-030-99739-7_3(22-30)Online publication date: 5-Apr-2022
https://doi.org/10.1007/978-3-030-99739-7_3
Lin ZKe HWong NBai JSong YZhao HYe JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Multi-Relational Graph based Heterogeneous Multi-Task Learning in Community Question AnsweringProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482279(1038-1047)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482279
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