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Modeling the dynamics of personal expertise

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SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval

Pages 1107 - 1110

https://doi.org/10.1145/2600428.2609521

Published: 03 July 2014 Publication History

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Abstract

Personal expertise or interests often evolve over time. Despite much work on expertise retrieval in the recent years, very little work has studied the dynamics of personal expertise. In this paper, we propose a probabilistic model to characterize how people change or stick with their expertise. Specifically, three factors are taken into consideration in whether an expert will choose a new expertise area: 1) the personality of the expert in exploring new areas; 2) the similarity between the new area and the expert's current areas; 3) the popularity of the new area. These three factors are integrated into a unified generative process. A predictive language model is derived to estimate the distribution of the expert's words in her future publications. In addition, KL divergence is defined on the predictive language model to quantify and forecast the change of expertise. We conduct the experiments on a testbed of academic publications and the initial results demonstrate the effectiveness of the proposed approach.

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Cited By

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Mau TLe QVo DDoan DHuynh V(2023)Integrating Machine Learning and Evidential Reasoning for User Profiling and RecommendationJournal of Systems Science and Systems Engineering10.1007/s11518-023-5569-532:4(393-412)Online publication date: 13-Jun-2023
https://doi.org/10.1007/s11518-023-5569-5
Liang SLuo YMeng Z(2021)Profiling Users for Question Answering Communities via Flow-Based Constrained Co-Embedding ModelACM Transactions on Information Systems10.1145/347056540:2(1-38)Online publication date: 24-Nov-2021
https://dl.acm.org/doi/10.1145/3470565
Meng ZLiang SZhang XMcCreadie ROunis I(2020)Jointly Learning Representations of Nodes and Attributes for Attributed NetworksACM Transactions on Information Systems10.1145/337785038:2(1-32)Online publication date: 27-Jan-2020
https://dl.acm.org/doi/10.1145/3377850
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Index Terms

Modeling the dynamics of personal expertise
1. Information systems
  1. Information retrieval

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Published In

SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval

July 2014

1330 pages

ISBN:9781450322577

DOI:10.1145/2600428

General Chairs:
Shlomo Geva
Queensland University of Technology
,
Andrew Trotman
University of Dunedin
,
Program Chairs:
Peter Bruza
Queensland University of Technology
,
Charles L.A. Clarke
University of Waterloo
,
Kal Järvelin
University of Tampere

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: 03 July 2014

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SIGIR '14

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SIGIR

SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 6 - 11, 2014

Queensland, Gold Coast, Australia

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SIGIR '14 Paper Acceptance Rate 82 of 387 submissions, 21%;

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

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Cited By

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Mau TLe QVo DDoan DHuynh V(2023)Integrating Machine Learning and Evidential Reasoning for User Profiling and RecommendationJournal of Systems Science and Systems Engineering10.1007/s11518-023-5569-532:4(393-412)Online publication date: 13-Jun-2023
https://doi.org/10.1007/s11518-023-5569-5
Liang SLuo YMeng Z(2021)Profiling Users for Question Answering Communities via Flow-Based Constrained Co-Embedding ModelACM Transactions on Information Systems10.1145/347056540:2(1-38)Online publication date: 24-Nov-2021
https://dl.acm.org/doi/10.1145/3470565
Meng ZLiang SZhang XMcCreadie ROunis I(2020)Jointly Learning Representations of Nodes and Attributes for Attributed NetworksACM Transactions on Information Systems10.1145/337785038:2(1-32)Online publication date: 27-Jan-2020
https://dl.acm.org/doi/10.1145/3377850
Luo YLiang SMeng ZZhu WTao DCheng XCui PRundensteiner ECarmel DHe QXu Yu J(2019)Constrained Co-embedding Model for User Profiling in Question Answering CommunitiesProceedings of the 28th ACM International Conference on Information and Knowledge Management10.1145/3357384.3358056(439-448)Online publication date: 3-Nov-2019
https://dl.acm.org/doi/10.1145/3357384.3358056
Gonçalves RDorneles C(2019)Automated Expertise RetrievalACM Computing Surveys10.1145/333100052:5(1-30)Online publication date: 13-Sep-2019
https://dl.acm.org/doi/10.1145/3331000
Meng ZLiang SBao HZhang XCulpepper JMoffat ABennett PLerman K(2019)Co-Embedding Attributed NetworksProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3291015(393-401)Online publication date: 30-Jan-2019
https://dl.acm.org/doi/10.1145/3289600.3291015
Liang SZhang XRen ZKanoulas EGuo YFarooq F(2018)Dynamic Embeddings for User Profiling in TwitterProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3220043(1764-1773)Online publication date: 19-Jul-2018
https://dl.acm.org/doi/10.1145/3219819.3220043
Van Gysel Cde Rijke MWorring MBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Unsupervised, Efficient and Semantic Expertise RetrievalProceedings of the 25th International Conference on World Wide Web10.1145/2872427.2882974(1069-1079)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.1145/2872427.2882974
Van Gysel Cde Rijke MWorring MBalog KDalton JDoucet AIbrahim Y(2015)Semantic EntitiesProceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval10.1145/2810133.2810139(1-2)Online publication date: 22-Oct-2015
https://dl.acm.org/doi/10.1145/2810133.2810139
Ribeiro ISantos RGonçalves MLaender ACheng XLi HGabrilovich ETang J(2015)On Tag Recommendation for Expertise ProfilingProceedings of the Eighth ACM International Conference on Web Search and Data Mining10.1145/2684822.2685320(189-198)Online publication date: 2-Feb-2015
https://dl.acm.org/doi/10.1145/2684822.2685320

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Automated Expertise Retrieval: A Taxonomy-Based Survey and Open Issues

Extending domain expertise through student modeling

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