A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature

He Zhao, Zhunchen Luo, Chong Feng, Anqing Zheng, Xiaopeng Liu


Abstract
We introduce a new task of modeling the role and function for on-line resource citations in scientific literature. By categorizing the on-line resources and analyzing the purpose of resource citations in scientific texts, it can greatly help resource search and recommendation systems to better understand and manage the scientific resources. For this novel task, we are the first to create an annotation scheme, which models the different granularity of information from a hierarchical perspective. And we construct a dataset SciRes, which includes 3,088 manually annotated resource contexts. In this paper, we propose a possible solution by using a multi-task framework to build the scientific resource classifier (SciResCLF) for jointly recognizing the role and function types. Then we use the classification results to help a scientific resource recommendation (SciResREC) task. Experiments show that our model achieves the best results on both the classification task and the recommendation task. The SciRes dataset is released for future research.
Anthology ID:
D19-1524
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
5206–5215
Language:
URL:
https://aclanthology.org/D19-1524
DOI:
10.18653/v1/D19-1524
Bibkey:
Cite (ACL):
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), pages 5206–5215, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature (Zhao et al., EMNLP 2019)
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