Abstract
With the rapid growth of scientific literature, it is becoming increasingly difficult to identify scientific contribution from the deluge of research papers. Automatically identifying the specific contribution made in a research paper would help quicker comprehension of the work, faster literature survey, comparison with the related works, etc. Here in this work, we investigate methods to automatically extract the contribution statements from research articles. We design a multitask deep neural network leveraging section identification and citance classification of scientific statements to predict whether a given scientific statement specifies a contribution or not. In the long-run, we envisage to create a knowledge graph of scientific contributions for machine comprehension and more straightforward navigation of research contributions in a particular domain. Our approach achieves the best performance over earlier methods (a relative improvement of 8.08% in terms of F1 score) for contributing sentence identification over a dataset of Natural Language Processing (NLP) papers. We make our code available at here (https://github.com/ammaarahmad1999/Sem-Eval-2021-Task-A ).
Original language | English |
---|---|
Title of host publication | Towards Open and Trustworthy Digital Societies - 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Proceedings |
Editors | Hao-Ren Ke, Chei Sian Lee, Kazunari Sugiyama |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 436-452 |
Number of pages | 17 |
ISBN (Print) | 9783030916688 |
DOIs | |
State | Published - 2021 |
Externally published | Yes |
Event | 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021 - Virtual, Online Duration: Dec 1 2021 → Dec 3 2021 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 13133 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021 |
---|---|
City | Virtual, Online |
Period | 12/1/21 → 12/3/21 |
Funding
Acknowledgement. Asif Ekbal is a recipient of the Visvesvaraya Young Faculty Award and acknowledges Digital India Corporation, Ministry of Electronics and Information Technology, Government of India for supporting this research.
Keywords
- Contribution identification
- Information extraction
- Multitask learning