Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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OriginalspracheEnglisch
Titel des SammelwerksTowards Open and Trustworthy Digital Societies
Untertitel23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings
Herausgeber/-innenHao-Ren Ke, Chei Sian Lee, Kazunari Sugiyama
ErscheinungsortCham
Herausgeber (Verlag)Springer Nature Switzerland AG
Seiten401-410
Seitenumfang10
ISBN (elektronisch)978-3-030-91669-5
ISBN (Print)9783030916688
PublikationsstatusVeröffentlicht - 2021
Veranstaltung23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021 - Virtual, Online
Dauer: 1 Dez. 20213 Dez. 2021

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band13133
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Abstract

We describe a rule-based approach for the automatic acquisition of salient scientific entities from Computational Linguistics (CL) scholarly article titles. Two observations motivated the approach: (i) noting salient aspects of an article’s contribution in its title; and (ii) pattern regularities capturing the salient terms that could be expressed in a set of rules. Only those lexico-syntactic patterns were selected that were easily recognizable, occurred frequently, and positionally indicated a scientific entity type. The rules were developed on a collection of 50,237 CL titles covering all articles in the ACL Anthology. In total, 19,799 research problems, 18,111 solutions, 20,033 resources, 1,059 languages, 6,878 tools, and 21,687 methods were extracted at an average precision of 75%.

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Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles. / D’Souza, Jennifer; Auer, Sören.
Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings. Hrsg. / Hao-Ren Ke; Chei Sian Lee; Kazunari Sugiyama. Cham: Springer Nature Switzerland AG, 2021. S. 401-410 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13133).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

D’Souza, J & Auer, S 2021, Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles. in H-R Ke, CS Lee & K Sugiyama (Hrsg.), Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 13133, Springer Nature Switzerland AG, Cham, S. 401-410, 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Virtual, Online, 1 Dez. 2021. https://doi.org/10.1007/978-3-030-91669-5_31
D’Souza, J., & Auer, S. (2021). Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles. In H.-R. Ke, C. S. Lee, & K. Sugiyama (Hrsg.), Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings (S. 401-410). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13133). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-91669-5_31
D’Souza J, Auer S. Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles. in Ke HR, Lee CS, Sugiyama K, Hrsg., Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings. Cham: Springer Nature Switzerland AG. 2021. S. 401-410. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Nov 30. doi: 10.1007/978-3-030-91669-5_31
D’Souza, Jennifer ; Auer, Sören. / Pattern-Based Acquisition of Scientific Entities from Scholarly Article Titles. Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings. Hrsg. / Hao-Ren Ke ; Chei Sian Lee ; Kazunari Sugiyama. Cham : Springer Nature Switzerland AG, 2021. S. 401-410 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "We describe a rule-based approach for the automatic acquisition of salient scientific entities from Computational Linguistics (CL) scholarly article titles. Two observations motivated the approach: (i) noting salient aspects of an article{\textquoteright}s contribution in its title; and (ii) pattern regularities capturing the salient terms that could be expressed in a set of rules. Only those lexico-syntactic patterns were selected that were easily recognizable, occurred frequently, and positionally indicated a scientific entity type. The rules were developed on a collection of 50,237 CL titles covering all articles in the ACL Anthology. In total, 19,799 research problems, 18,111 solutions, 20,033 resources, 1,059 languages, 6,878 tools, and 21,687 methods were extracted at an average precision of 75%.",
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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).

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