Team MLU@CL-SciSumm20: Methods for Computational Linguistics Scientific Citation Linkage

Rong Huang, Kseniia Krylova


Abstract
This paper describes our approach to the CL-SciSumm 2020 shared task toward the problem of identifying reference span of the citing article in the referred article. In Task 1a, we apply and compare different methods in combination with similarity scores to identify spans of the reference text for the given citance. In Task 1b, we use a logistic regression to classifying the discourse facets.
Anthology ID:
2020.sdp-1.32
Volume:
Proceedings of the First Workshop on Scholarly Document Processing
Month:
November
Year:
2020
Address:
Online
Editors:
Muthu Kumar Chandrasekaran, Anita de Waard, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Eduard Hovy, Petr Knoth, David Konopnicki, Philipp Mayr, Robert M. Patton, Michal Shmueli-Scheuer
Venue:
sdp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
282–287
Language:
URL:
https://aclanthology.org/2020.sdp-1.32
DOI:
10.18653/v1/2020.sdp-1.32
Bibkey:
Cite (ACL):
Rong Huang and Kseniia Krylova. 2020. Team MLU@CL-SciSumm20: Methods for Computational Linguistics Scientific Citation Linkage. In Proceedings of the First Workshop on Scholarly Document Processing, pages 282–287, Online. Association for Computational Linguistics.
Cite (Informal):
Team MLU@CL-SciSumm20: Methods for Computational Linguistics Scientific Citation Linkage (Huang & Krylova, sdp 2020)
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PDF:
https://aclanthology.org/2020.sdp-1.32.pdf