Details
| Original language | English |
|---|---|
| Title of host publication | From Born-Physical to Born-Virtual |
| Subtitle of host publication | Augmenting Intelligence in Digital Libraries - 24th International Conference on Asian Digital Libraries, ICADL 2022, Proceedings |
| Editors | Yuen-Hsien Tseng, Marie Katsurai, Hoa N. Nguyen |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 35-45 |
| Number of pages | 11 |
| ISBN (print) | 9783031217555 |
| Publication status | Published - 7 Dec 2022 |
| Event | 24th International Conference on Asia-Pacific Digital Libraries, ICADL 2022 - Hanoi, Viet Nam Duration: 30 Nov 2022 → 2 Dec 2022 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 13636 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Domain-specific named entity recognition (NER) on Computer Science (CS) scholarly articles is an information extraction task that is arguably more challenging for the various annotation aims that can hamper the task and has been less studied than NER in the general domain. Given that significant progress has been made on NER, we anticipate that scholarly domain-specific NER will receive increasing attention in the years to come. Currently, progress on CS NER – the focus of this work – is hampered in part by its recency and the lack of a standardized annotation aims for scientific entities/terms. Directly addressing these issues, this work proposes a standardized task by defining a set of seven contribution-centric scholarly entities for CS NER viz., research problem, solution, resource, language, tool, method, and dataset.
Keywords
- Information extraction, Named entity recognition
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
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From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries - 24th International Conference on Asian Digital Libraries, ICADL 2022, Proceedings. ed. / Yuen-Hsien Tseng; Marie Katsurai; Hoa N. Nguyen. Springer Science and Business Media Deutschland GmbH, 2022. p. 35-45 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13636 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Computer Science Named Entity Recognition in the Open Research Knowledge Graph
AU - D’Souza, Jennifer
AU - Auer, Sören
N1 - Funding Information: Supported by TIB Leibniz Information Centre for Science and Technology, the EU H2020 ERC project ScienceGRaph (GA ID: 819536).
PY - 2022/12/7
Y1 - 2022/12/7
N2 - Domain-specific named entity recognition (NER) on Computer Science (CS) scholarly articles is an information extraction task that is arguably more challenging for the various annotation aims that can hamper the task and has been less studied than NER in the general domain. Given that significant progress has been made on NER, we anticipate that scholarly domain-specific NER will receive increasing attention in the years to come. Currently, progress on CS NER – the focus of this work – is hampered in part by its recency and the lack of a standardized annotation aims for scientific entities/terms. Directly addressing these issues, this work proposes a standardized task by defining a set of seven contribution-centric scholarly entities for CS NER viz., research problem, solution, resource, language, tool, method, and dataset.
AB - Domain-specific named entity recognition (NER) on Computer Science (CS) scholarly articles is an information extraction task that is arguably more challenging for the various annotation aims that can hamper the task and has been less studied than NER in the general domain. Given that significant progress has been made on NER, we anticipate that scholarly domain-specific NER will receive increasing attention in the years to come. Currently, progress on CS NER – the focus of this work – is hampered in part by its recency and the lack of a standardized annotation aims for scientific entities/terms. Directly addressing these issues, this work proposes a standardized task by defining a set of seven contribution-centric scholarly entities for CS NER viz., research problem, solution, resource, language, tool, method, and dataset.
KW - Information extraction
KW - Named entity recognition
UR - http://www.scopus.com/inward/record.url?scp=85145006145&partnerID=8YFLogxK
U2 - https://doi.org/10.48550/arXiv.2203.14579
DO - https://doi.org/10.48550/arXiv.2203.14579
M3 - Conference contribution
AN - SCOPUS:85145006145
SN - 9783031217555
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 35
EP - 45
BT - From Born-Physical to Born-Virtual
A2 - Tseng, Yuen-Hsien
A2 - Katsurai, Marie
A2 - Nguyen, Hoa N.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th International Conference on Asia-Pacific Digital Libraries, ICADL 2022
Y2 - 30 November 2022 through 2 December 2022
ER -