research-article

Coopetition in IR research

Author: Ellen M. VoorheesAuthors Info & Claims

Article No.: 1, Pages 1 - 3

Published: 20 August 2021 Publication History

Abstract

Coopetition is defined as competitors cooperating for the common good, an apt description of the community evaluations such as TREC that build infrastructure to support information retrieval (IR) research. This note summarizes the main points of a keynote talk presented at SIGIR 2020 that looks at the benefits and risks coopetition can engender in IR research.

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Chamorro-Padial JRodrigo-Ginés FRodríguez-Sánchez R(2024)Finding answers to COVID-19-specific questionsJournal of Information Science10.1177/0165551522111099550:4(935-951)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1177/01655515221110995
Young OFan YZhang RGuo Jde Rijke MCheng XSerra ESpezzano F(2024)GaQR: An Efficient Generation-augmented Question RewriterProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679930(4228-4232)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679930
Ekstrand MCarterette BDiaz F(2024)Distributionally-Informed Recommender System EvaluationACM Transactions on Recommender Systems10.1145/36134552:1(1-27)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3613455
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Coopetition in IR research
1. Information systems
  1. Information retrieval

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Published In

ACM SIGIR Forum Volume 54, Issue 2

December 2020

115 pages

ISSN:0163-5840

DOI:10.1145/3483382

Issue’s Table of Contents

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 August 2021

Published in SIGIR Volume 54, Issue 2

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Chamorro-Padial JRodrigo-Ginés FRodríguez-Sánchez R(2024)Finding answers to COVID-19-specific questionsJournal of Information Science10.1177/0165551522111099550:4(935-951)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1177/01655515221110995
Young OFan YZhang RGuo Jde Rijke MCheng XSerra ESpezzano F(2024)GaQR: An Efficient Generation-augmented Question RewriterProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679930(4228-4232)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679930
Ekstrand MCarterette BDiaz F(2024)Distributionally-Informed Recommender System EvaluationACM Transactions on Recommender Systems10.1145/36134552:1(1-27)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3613455
Fröbe MReimer JMacAvaney SDeckers NReich SBevendorff JStein BHagen MPotthast MChen HDuh WHuang HKato MMothe JPoblete B(2023)The Information Retrieval Experiment PlatformProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591888(2826-2836)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591888
Church KKordoni V(2022)Emerging Trends: SOTA-ChasingNatural Language Engineering10.1017/S135132492200004328:2(249-269)Online publication date: 8-Feb-2022
https://doi.org/10.1017/S1351324922000043
Lawrie DMayfield JOard DYang E(2022)HC4: A New Suite of Test Collections for Ad Hoc CLIRAdvances in Information Retrieval10.1007/978-3-030-99736-6_24(351-366)Online publication date: 10-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-030-99736-6_24
Moro GValgimigli L(2021)Efficient Self-Supervised Metric Information Retrieval: A Bibliography Based Method Applied to COVID LiteratureSensors10.3390/s2119643021:19(6430)Online publication date: 26-Sep-2021
https://doi.org/10.3390/s21196430
Frommholz ICabanac GMayr PVerberne S(2021)Report on the 11th bibliometric-enhanced information retrieval workshop (BIR 2021)ACM SIGIR Forum10.1145/3476415.347642655:1(1-9)Online publication date: 16-Jul-2021
https://dl.acm.org/doi/10.1145/3476415.3476426
Han XLiu YLin JHasibi FFang YAizawa A(2021)The Simplest Thing That Can Possibly Work: (Pseudo-)Relevance Feedback via Text ClassificationProceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3471158.3472261(123-129)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3471158.3472261
Rybinski MKarimi SDemartini GZuccon GCulpepper JHuang ZTong H(2021)Will Sorafenib Help?Proceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482220(3403-3407)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482220
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