
Suchetha N. Kunnath
PhD Research Student
Suchetha is a Jisc funded PhD student at KMi, part of the Big Scientific Data and Text Analytics Group (BSDTAG) team: http://bsdtag.kmi.open.ac.uk/. Her research is focussed on the classification of citations based on their functions for impact assessment.
Keywords
Text Mining, Machine Learning, Natural Language Processing
Publications
Nambanoor Kunnath, Suchetha, Pride, David and Knoth, Petr(2023). Prompting Strategies for Citation Classification. In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM '23), Birmingham, United Kingdom, pp. 1127–1137.
Nambanoor Kunnath, Suchetha, Pride, David and Knoth, Petr(2022). Dynamic Context Extraction for Citation Classification. In: The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 20-23 Nov 2022, Virtual.
Nambanoor Kunnath, Suchetha, Stauber, Valentin, Wu, Ronin, Pride, David , Botev, Viktor and Knoth, Petr(2022). ACT2: A multi-disciplinary semi-structured dataset for importance and purpose classification of citations. In: Proceedings of the 13th Language Resources and Evaluation Conference, Association for Computational Linguistics.
Kunnath, Suchetha N., Herrmannova, Drahomira , Pride, David and Knoth, Petr(2022). A Meta-analysis of Semantic Classification of Citations. Quantitative Science Studies, 2(4) pp. 1170–1215.
Kunnath, Suchetha N., Pride, David , Herrmannova, Drahomira and Knoth, Petr(2021). Overview of the 2021 SDP 3C Citation Context Classification Shared Task. In: Proceedings of the Second Workshop on Scholarly Document Processing, Association for Computational Linguistics, Stroudsburg, PA, pp. 150–158.
Kunnath, Suchetha N., Pride, David , Gyawali, Bikash and Knoth, Petr(2020). Overview of the 2020 WOSP 3C Citation Context Classification Task. In: Proceedings of the 8th International Workshop on Mining Scientific Publications, Association for Computational Linguistics pp. 75–83.
Themes
Artificial Intelligence and Data AnalysisTopics
Science and scholarly communication