abstract

Extraction and Evaluation of Knowledge Entities from Scientific Documents: EEKE2020

Authors:

Chengzhi Zhang,

Yi ZhangAuthors Info & Claims

JCDL '20: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020

Pages 573 - 574

https://doi.org/10.1145/3383583.3398504

Published: 01 August 2020 Publication History

Abstract

The goal of this workshop is to engage the related communities in open problems in the extraction and evaluation of knowledge entities from scientific documents. This workshop entitles this cutting-edge and cross-disciplinary direction Extraction and Evaluation of Knowledge Entity (EEKE), highlighting the development of intelligent methods for identifying knowledge claims in scientific documents, and promoting the application of knowledge entities. The website of this workshop is at: https://eeke2020.github.io/.

References

[1]

Iana Atanassova, Marc Bertin, and Philipp Mayr. 2019. Editorial: Mining Scientific Papers: NLP-enhanced Bibliometrics. Frontiers in Research Metrics and Analytics (2019). https://doi.org/10.3389/frma.2019.00002

[2]

Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007. Dbpedia: A nucleus for a web of open data. In The semantic web. Springer, 722--735.

Digital Library

[3]

Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, and Andrew McCallum. 2017. SemEval 2017 Task 10: ScienceIE-Extracting Keyphrases and Relations from Scientific Publications. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). 546--555.

[4]

Katarina Boland and Frank Krüger. 2019. Distant supervision for silver label generation of software mentions in social scientific publications. In Proc. Joint Workshop Bibliometric-Enhanced Inf. Retrieval Nat. Lang. Process. Digit. Libraries. 15--27.

[5]

Arthur Brack, Jennifer D'Souza, Anett Hoppe, Sören Auer, and Ralph Ewerth. 2020. Domain-independent Extraction of Scientific Concepts from Research Articles. arXiv preprint arXiv:2001.03067 (2020).

[6]

Xiao Chang and Qinghua Zheng. 2007. Knowledge element extraction for knowledge-based learning resources organization. In International Conference on Web-Based Learning. Springer, 102--113.

[7]

Ruiyi Ding, Yuzhuo Wang, and Chengzhi Zhang. 2019. Investigating Citation of Algorithm in Full-text of Academic Articles in NLP domain: A Preliminary Study. In Proceedings of the 17th International Conference on Scientometrics and Informetrics. 2726--2727.

[8]

Ying Ding, Min Song, Jia Han, Qi Yu, Erjia Yan, Lili Lin, and Tamy Chambers. 2013. Entitymetrics: Measuring the impact of entities. PloS one 8, 8 (2013).

[9]

Yufang Hou, Charles Jochim, Martin Gleize, Francesca Bonin, and Debasis Ganguly. 2019. Identification of Tasks, Datasets, Evaluation Metrics, and Numeric Scores for Scientific Leaderboards Construction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 5203--5213.

[10]

Aleksandar Kovaevic, Zora Konjovic, Branko Milosavljevi?, and Goran Nenadic. 2012. Mining methodologies from NLP publications: A case study in automatic terminology recognition. Computer Speech & Language 26, 2 (2012), 105--126.

Digital Library

[11]

Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018. Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 3219--3232.

[12]

Philipp Mayr, Ingo Frommholz, Guillaume Cabanac, Muthu Kumar Chandrasekaran, Kokil Jaidka, Min-Yen Kan, and DietmarWolfram. 2018. Introduction to the Special Issue on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL). International Journal on Digital Libraries (2018). https://doi.org/10.1007/s00799-017-0230-x

[13]

Suppawong Tuarob, Sung Kang, Poom Wettayakorn, Chanatip Pornprasit, Tanakitti Sachati, Saeed-Ul Hassan, and Peter Haddawy. 2020. Automatic Classification of Algorithm Citation Functions in Scientific Literature. IEEE Transactions on Knowledge and Data Engineering (2020). https://doi.org/10.1109/TKDE.2019. 2913376

[14]

Yuzhuo Wang and Chengzhi Zhang. 2019. Finding More Methodological Entities from Academic Articles via Iterative Strategy: A Preliminary Study. In Proceedings of the 17th International Conference on Scientometrics and Informetrics. 2702--2703.

[15]

Hanwen Zha, Wenhu Chen, Keqian Li, and Xifeng Yan. 2019. Mining Algorithm Roadmap in Scientific Publications. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 1083--1092.

Digital Library

[16]

He Zhao, Zhunchen Luo, Chong Feng, Anqing Zheng, and Xiaopeng Liu. 2019. A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 5209--5218

Cited By

Percia David DMaréchal LLacube WGillard STsesmelis MMaillart TMermoud A(2023)Measuring security development in information technologies: A scientometric framework using arXiv e-printsTechnological Forecasting and Social Change10.1016/j.techfore.2023.122316188(122316)Online publication date: Mar-2023
https://doi.org/10.1016/j.techfore.2023.122316
Zhang CMayr PLu WZhang YAizawa AMandl TCarevic ZHinze AMayr PSchaer P(2022)JCDL2022 workshopProceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries10.1145/3529372.3530917(1-2)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1145/3529372.3530917
Zhang YZhang CMayr PSuominen A(2022)An editorial of “AI + informetrics”: multi-disciplinary interactions in the era of big dataScientometrics10.1007/s11192-022-04561-w127:11(6503-6507)Online publication date: 17-Oct-2022
https://doi.org/10.1007/s11192-022-04561-w
Show More Cited By

Index Terms

Extraction and Evaluation of Knowledge Entities from Scientific Documents: EEKE2020
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Information extraction

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Information & Contributors

Information

Published In

cover image ACM Conferences

JCDL '20: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020

August 2020

611 pages

ISBN:9781450375856

DOI:10.1145/3383583

General Chairs:
Ruhua Huang
Wuhan University, China
,
Dan Wu
Wuhan University, China
,
Gary Marchionini
University of North Carolina at Chapel Hill, USA
,
Program Chairs:
Daqing He
University of Pittsburgh, USA
,
Sally Jo Cunningham
University of Waikato, New Zealand
,
Preben Hansen
Stockholm University, Sweden

Copyright © 2020 Owner/Author.

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.

Sponsors

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
IEEE: Institute of Electrical and Electronics Engineers

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2020

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Conference

JCDL '20

Sponsor:

JCDL '20: The ACM/IEEE Joint Conference on Digital Libraries in 2020

August 1 - 5, 2020

Virtual Event, China

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

Percia David DMaréchal LLacube WGillard STsesmelis MMaillart TMermoud A(2023)Measuring security development in information technologies: A scientometric framework using arXiv e-printsTechnological Forecasting and Social Change10.1016/j.techfore.2023.122316188(122316)Online publication date: Mar-2023
https://doi.org/10.1016/j.techfore.2023.122316
Zhang CMayr PLu WZhang YAizawa AMandl TCarevic ZHinze AMayr PSchaer P(2022)JCDL2022 workshopProceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries10.1145/3529372.3530917(1-2)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1145/3529372.3530917
Zhang YZhang CMayr PSuominen A(2022)An editorial of “AI + informetrics”: multi-disciplinary interactions in the era of big dataScientometrics10.1007/s11192-022-04561-w127:11(6503-6507)Online publication date: 17-Oct-2022
https://doi.org/10.1007/s11192-022-04561-w
Zhang CMayr PLu WZhang Y(2021)Extraction and Evaluation of Knowledge Entities from Scientific DocumentsJournal of Data and Information Science10.2478/jdis-2021-00256:3(1-5)Online publication date: 9-Aug-2021
https://doi.org/10.2478/jdis-2021-0025
Zhang CMayr PLu WZhang Y(2021)Knowledge Entity Extraction and Text Mining in the Era of Big DataData and Information Management10.2478/dim-2021-00095:3(309-311)Online publication date: 2-Jul-2021
https://doi.org/10.2478/dim-2021-0009
Savinitch LZhozhikashvilly AStefanuk V(2021)Logic Theory of Text ContentsProceedings of the Fifth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’21)10.1007/978-3-030-87178-9_12(119-127)Online publication date: 16-Sep-2021
https://doi.org/10.1007/978-3-030-87178-9_12

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