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Towards expert finding by leveraging relevant categories in authority ranking

Published: 24 October 2011 Publication History

Abstract

How to improve authority ranking is a crucial research problem for expert finding. In this paper, we propose a novel framework for expert finding based on the authority information in the target category as well as the relevant categories. First, we develop a scalable method for measuring the relevancy between categories through topic models. Then, we provide a link analysis approach for ranking user authority by considering the information in both the target category and the relevant categories. Finally, the extensive experiments on two large-scale real-world Q&A data sets clearly show that the proposed method outperforms the baseline methods with a significant margin.

References

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T. Bao, H. Cao, E. Chen, J. Tian, and H. Xiong. An unsupervised approach to modeling personalized contexts of mobile users. In ICDM'10.
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D. M. Blei, A. Y. Ng, and M. I. Jordan. Lantent dirichlet allocation. In Journal of Machine Learning Research.
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Y. Liu, J. Bian, and E. Agichtein. Predicting information seeker satisfaction in community question answering. In SIGIR'08.
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L. Nie, B. D. Davison, and X. Qi. Topical link analysis for web search. In In SIGIR'06.
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J. Zhang, M. S. Ackerman, and L. Adamic. Expertise networks in online communities: structure and algorithms. In WWW'07.

Cited By

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  • (2024)PEPT: Expert Finding Meets Personalized Pre-TrainingACM Transactions on Information Systems10.1145/369038043:1(1-26)Online publication date: 28-Aug-2024
  • (2024)A Study of Expert Finding Methods for Multi-Granularity Encoded Community Question Answering by Fusing Graph Neural NetworksIEEE Access10.1109/ACCESS.2024.345054412(142168-142180)Online publication date: 2024
  • (2024)MATERExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121576237:PBOnline publication date: 1-Feb-2024
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        cover image ACM Conferences
        CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
        October 2011
        2712 pages
        ISBN:9781450307178
        DOI:10.1145/2063576
        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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        New York, NY, United States

        Publication History

        Published: 24 October 2011

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        Author Tags

        1. authority ranking
        2. category relevancy
        3. expert finding;
        4. topic models

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

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        Cited By

        View all
        • (2024)PEPT: Expert Finding Meets Personalized Pre-TrainingACM Transactions on Information Systems10.1145/369038043:1(1-26)Online publication date: 28-Aug-2024
        • (2024)A Study of Expert Finding Methods for Multi-Granularity Encoded Community Question Answering by Fusing Graph Neural NetworksIEEE Access10.1109/ACCESS.2024.345054412(142168-142180)Online publication date: 2024
        • (2024)MATERExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121576237:PBOnline publication date: 1-Feb-2024
        • (2023)Feature-Alignment-Based Cross-Platform Question Answering Expert RecommendationMathematics10.3390/math1109217411:9(2174)Online publication date: 5-May-2023
        • (2023)A deep learning-based expert finding method to retrieve agile software teams from CQAsInformation Processing & Management10.1016/j.ipm.2022.10314460:2(103144)Online publication date: Mar-2023
        • (2021)LDA-based term profiles for expert finding in a political settingJournal of Intelligent Information Systems10.1007/s10844-021-00636-xOnline publication date: 23-Mar-2021
        • (2021)Time-aware hybrid expertise retrieval system in community question answering servicesApplied Intelligence10.1007/s10489-020-02177-2Online publication date: 17-Feb-2021
        • (2020)Helping the Ineloquent Farmers: Finding Experts for Questions With Limited Text in Agricultural Q&A CommunitiesIEEE Access10.1109/ACCESS.2020.29843428(62238-62247)Online publication date: 2020
        • (2019)Expert recommendation in community question answering: a review and future directionInternational Journal of Crowd Science10.1108/IJCS-03-2019-00113:3(348-372)Online publication date: 2-Sep-2019
        • (2019)Cultivating Online: Understanding Expert and Farmer Participation in an Agricultural Q&A CommunityComputer Supported Cooperative Work and Social Computing10.1007/978-981-15-1377-0_26(335-350)Online publication date: 14-Nov-2019
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