abstract

Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2019)

Authors:

Muthu Kumar Chandrasekaran,

Min-Yen KanAuthors Info & Claims

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1441 - 1443

https://doi.org/10.1145/3331184.3331650

Published: 18 July 2019 Publication History

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Abstract

The deluge of scholarly publication poses a challenge for scholars find relevant research and policy makers to seek in-depth information and understand research impact. Information retrieval (IR), natural language processing (NLP) and bibliometrics could enhance scholarly search, retrieval and user experience, but their use in digital libraries is not widespread. To address this gap, we propose the 4th Joint Workshop on BIRNDL and the 5th CL-SciSumm Shared Task. We seek to foster collaboration among researchers in NLP, IR and Digital Libraries (DL), and to stimulate the development of new methods in NLP, IR, recommendation systems and scientometrics toward improved scholarly document understanding, analysis, and retrieval at scale.

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Guillaume Cabanac, Muthu Kumar Chandrasekaran, Ingo Frommholz, Kokil Jaidka, Min-Yen Kan, Philipp Mayr, and Dietmar Wolfram. 2016. Report on the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016). SIGIR Forum, Vol. 50, 2 (2016), 36--43. http://sigir.org/wp-content/uploads/2017/01/p036.pdf

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Cited By

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Ramesh Kashyap AYang YKan M(2023)Scientific document processing: challenges for modern learning methodsInternational Journal on Digital Libraries10.1007/s00799-023-00352-724:4(283-309)Online publication date: 24-Mar-2023
https://doi.org/10.1007/s00799-023-00352-7
Chandrasekaran MMayr P(2021)Report on the 4th Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries at SIGIR 2019ACM SIGIR Forum10.1145/3458553.345855453:2(3-10)Online publication date: 23-Mar-2021
https://dl.acm.org/doi/10.1145/3458553.3458554
La Quatra MCagliero LBaralis E(2021)Leveraging full-text article exploration for citation analysisScientometrics10.1007/s11192-021-04117-4Online publication date: 18-Aug-2021
https://doi.org/10.1007/s11192-021-04117-4
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Index Terms

Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2019)
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information retrieval
    1. Search engine architectures and scalability
      1. Link and co-citation analysis

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Information & Contributors

Information

Published In

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2019

1512 pages

ISBN:9781450361729

DOI:10.1145/3331184

General Chairs:
Benjamin Piwowarski
CNRS - Sorbonne Universite, France
,
Max Chevalier
Universite de Toulouse, CNRS, France
,
Eric Gaussier
Universite Grenoble Alpes, CNRS, France
,
Program Chairs:
Yoelle Maarek
Amazon Research, Israel
,
Jian-Yun Nie
University of Montreal, Canada
,
Falk Scholer
RMIT University, Australia

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.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 July 2019

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Abstract

Funding Sources

SRI International
Deutsche Forschungsgemeinschaft (DFG)
Chan-Zuckerberg Initiative

Conference

SIGIR '19

Sponsor:

SIGIR

SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 21 - 25, 2019

Paris, France

Acceptance Rates

SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;

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

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Citations

Cited By

View all

Ramesh Kashyap AYang YKan M(2023)Scientific document processing: challenges for modern learning methodsInternational Journal on Digital Libraries10.1007/s00799-023-00352-724:4(283-309)Online publication date: 24-Mar-2023
https://doi.org/10.1007/s00799-023-00352-7
Chandrasekaran MMayr P(2021)Report on the 4th Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries at SIGIR 2019ACM SIGIR Forum10.1145/3458553.345855453:2(3-10)Online publication date: 23-Mar-2021
https://dl.acm.org/doi/10.1145/3458553.3458554
La Quatra MCagliero LBaralis E(2021)Leveraging full-text article exploration for citation analysisScientometrics10.1007/s11192-021-04117-4Online publication date: 18-Aug-2021
https://doi.org/10.1007/s11192-021-04117-4
Feijo DMoreira V(2021)Improving abstractive summarization of legal rulings through textual entailmentArtificial Intelligence and Law10.1007/s10506-021-09305-431:1(91-113)Online publication date: 27-Nov-2021
https://doi.org/10.1007/s10506-021-09305-4
Fu YSchneider JHuang RWu DMarchionini GHe DCunningham SHansen P(2020)Towards Knowledge Maintenance in Scientific Digital Libraries with the Keystone FrameworkProceedings of the ACM/IEEE Joint Conference on Digital Libraries in 202010.1145/3383583.3398514(217-226)Online publication date: Aug-2020
https://doi.org/10.1145/3383583.3398514
Zhao LZhao ZXu HZhang YXu Y(2020)Visual Analysis and Mining of Knowledge Graph for Power Network Data Based on Natural Language Processing2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)10.1109/ICCMC48092.2020.ICCMC-00077(410-413)Online publication date: Mar-2020
https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00077
La Quatra MCagliero LBaralis E(2020)Exploiting pivot words to classify and summarize discourse facets of scientific papersScientometrics10.1007/s11192-020-03532-3Online publication date: 13-Jun-2020
https://doi.org/10.1007/s11192-020-03532-3
Zerva CNghiem MNguyen NAnaniadou S(2020)Cited text span identification for scientific summarisation using pre-trained encodersScientometrics10.1007/s11192-020-03455-zOnline publication date: 7-May-2020
https://doi.org/10.1007/s11192-020-03455-z
Saier TFärber M(2020)unarXive: a large scholarly data set with publications’ full-text, annotated in-text citations, and links to metadataScientometrics10.1007/s11192-020-03382-zOnline publication date: 2-Mar-2020
https://doi.org/10.1007/s11192-020-03382-z
Cabanac GFrommholz IMayr P(2020)Bibliometric-Enhanced Information Retrieval 10th Anniversary Workshop EditionAdvances in Information Retrieval10.1007/978-3-030-45442-5_85(641-647)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45442-5_85

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