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Citation Style Classification: a Comparison of Machine Learning Approaches. / Kopan, Artyom; Smirnova, Anna N.; Shchuckin, Ilya; Makeev, Vladislav; Chernishev, George A.

2023. 1058-1064 Paper presented at 2023 IEEE International Conference on Data Mining Workshops, Шанхай, China.

Research output: Contribution to conference › Paper › peer-review

Harvard

Kopan, A, Smirnova, AN, Shchuckin, I, Makeev, V & Chernishev, GA 2023, 'Citation Style Classification: a Comparison of Machine Learning Approaches', Paper presented at 2023 IEEE International Conference on Data Mining Workshops, Шанхай, China, 4/12/23 - 4/12/23 pp. 1058-1064. https://doi.org/10.1109/ICDMW60847.2023.00139, https://doi.org/10.1109/ICDMW60847.2023.00139

APA

Kopan, A., Smirnova, A. N., Shchuckin, I., Makeev, V., & Chernishev, G. A. (2023). Citation Style Classification: a Comparison of Machine Learning Approaches. 1058-1064. Paper presented at 2023 IEEE International Conference on Data Mining Workshops, Шанхай, China. https://doi.org/10.1109/ICDMW60847.2023.00139, https://doi.org/10.1109/ICDMW60847.2023.00139

Vancouver

Kopan A, Smirnova AN, Shchuckin I, Makeev V, Chernishev GA. Citation Style Classification: a Comparison of Machine Learning Approaches. 2023. Paper presented at 2023 IEEE International Conference on Data Mining Workshops, Шанхай, China. https://doi.org/10.1109/ICDMW60847.2023.00139, https://doi.org/10.1109/ICDMW60847.2023.00139

Author

Kopan, Artyom ; Smirnova, Anna N. ; Shchuckin, Ilya ; Makeev, Vladislav ; Chernishev, George A. / Citation Style Classification: a Comparison of Machine Learning Approaches. Paper presented at 2023 IEEE International Conference on Data Mining Workshops, Шанхай, China.7 p.

BibTeX

@conference{d31be7550b1b4ee68f539955aae5dab8,
title = "Citation Style Classification: a Comparison of Machine Learning Approaches",
abstract = "Citation style classification is a task that aims to detect a citation style according to which a given bibliographic entry is formatted. There are more than a hundred of recognized citation styles available, including popular ones such as ACM, IEEE, MLA, APA, and even more exotic ones. Automatic detection of citation style can be used in document linters, such as those intended for conference and term papers. Using automatic style classification enables people who assess articles in large quantities reduce cognitive load and increase efficiency. Apart from this, automatic detection of citation style can be used for reference parsing, topic classification, and reference extraction.In this paper we propose two novel approaches to citation style classification using both deep and classic machine learning methods. We evaluate them using a specially designed dataset, consisting of 6 million bibliographic records and spanning 91 citation styles. Our experiments showed that the proposed approaches significantly outperform the existing state-of-the-art solution, while also supporting almost five times more citation styles. {\textcopyright} 2023 IEEE.",
keywords = "citation, citation classification, citation style classification, reference classification, Deep learning, Automatic Detection, Bibliographic records, Citation, Citation classification, Citation style classification, Cognitive loads, Machine learning approaches, Machine learning methods, Reference classification, Topic Classification, Bibliographies",
author = "Artyom Kopan and Smirnova, {Anna N.} and Ilya Shchuckin and Vladislav Makeev and Chernishev, {George A.}",
note = "Код конференции: 197121 Export Date: 11 March 2024 Адрес для корреспонденции: Kopan, A.; Saint-Petersburg UniversityRussian Federation; эл. почта: artyom.kopan@gmail.com Пристатейные ссылки: Tkaczyk, D., (2019) What's your (citations') style?, , https://www.crossref.org/blog/whats-your-citations-style/; Schwartz, R., Dodge, J., Smith, N.A., Etzioni, O., Green ai (2020) Commun. ACM, 63 (12), pp. 54-63. , https://doi.org/10.1145/3381831, nov; Jochim, C., Sch{\"u}tze, H., Towards a generic and flexible citation classifier based on a faceted classification scheme (2012) Proceedings of COLING 2012, pp. 1343-1358; Moravcsik, M.J., Murugesan, P., Some results on the function and quality of citations (1975) Social studies of science, 5 (1), pp. 86-92; Dong, C., Sch{\"a}fer, U., Ensemble-style self-training on citation classification (2011) Proceedings of 5th international joint conference on natural language processing, pp. 623-631; Butt, B.H., Rafi, M., Jamal, A., Rehman, R.S.U., Alam, S.M.Z., Alam, M.B., (2015) Classification of research citations (crc); Nanba, H., Kando, N., Okumura, M., Classification of research papers using citation links and citation types: Towards automatic review article generation (2000) Advances in Classification Research Online, pp. 117-134; Cohen, A.M., Hersh, W.R., Peterson, K., Yen, P.-Y., Reducing workload in systematic review preparation using automated citation classification (2006) Journal of the American Medical Informatics Association, 13 (2), pp. 206-219; Lin, J., Song, J., Zhou, Z., Chen, Y., Shi, X., Automated scholarly paper review: Concepts, technologies, and challenges (2023) Information Fusion, 98, p. 101830. , https://www.sciencedirect.com/science/article/pii/S156625352300146X; Sanh, V., Debut, L., Chaumond, J., Wolf, T., (2019) Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter, , http://arxiv.org/abs/1910.01108, CoRR, Vol. abs/1910. 01108; 2023 IEEE International Conference on Data Mining Workshops, ICDMW ; Conference date: 04-12-2023 Through 04-12-2023",
year = "2023",
month = dec,
day = "4",
doi = "10.1109/ICDMW60847.2023.00139",
language = "English",
pages = "1058--1064",

}

RIS

TY - CONF

T1 - Citation Style Classification: a Comparison of Machine Learning Approaches

AU - Kopan, Artyom

AU - Smirnova, Anna N.

AU - Shchuckin, Ilya

AU - Makeev, Vladislav

AU - Chernishev, George A.

N1 - Conference code: 23

PY - 2023/12/4

Y1 - 2023/12/4

N2 - Citation style classification is a task that aims to detect a citation style according to which a given bibliographic entry is formatted. There are more than a hundred of recognized citation styles available, including popular ones such as ACM, IEEE, MLA, APA, and even more exotic ones. Automatic detection of citation style can be used in document linters, such as those intended for conference and term papers. Using automatic style classification enables people who assess articles in large quantities reduce cognitive load and increase efficiency. Apart from this, automatic detection of citation style can be used for reference parsing, topic classification, and reference extraction.In this paper we propose two novel approaches to citation style classification using both deep and classic machine learning methods. We evaluate them using a specially designed dataset, consisting of 6 million bibliographic records and spanning 91 citation styles. Our experiments showed that the proposed approaches significantly outperform the existing state-of-the-art solution, while also supporting almost five times more citation styles. © 2023 IEEE.

AB - Citation style classification is a task that aims to detect a citation style according to which a given bibliographic entry is formatted. There are more than a hundred of recognized citation styles available, including popular ones such as ACM, IEEE, MLA, APA, and even more exotic ones. Automatic detection of citation style can be used in document linters, such as those intended for conference and term papers. Using automatic style classification enables people who assess articles in large quantities reduce cognitive load and increase efficiency. Apart from this, automatic detection of citation style can be used for reference parsing, topic classification, and reference extraction.In this paper we propose two novel approaches to citation style classification using both deep and classic machine learning methods. We evaluate them using a specially designed dataset, consisting of 6 million bibliographic records and spanning 91 citation styles. Our experiments showed that the proposed approaches significantly outperform the existing state-of-the-art solution, while also supporting almost five times more citation styles. © 2023 IEEE.

KW - citation

KW - citation classification

KW - citation style classification

KW - reference classification

KW - Deep learning

KW - Automatic Detection

KW - Bibliographic records

KW - Citation

KW - Citation classification

KW - Citation style classification

KW - Cognitive loads

KW - Machine learning approaches

KW - Machine learning methods

KW - Reference classification

KW - Topic Classification

KW - Bibliographies

U2 - 10.1109/ICDMW60847.2023.00139

DO - 10.1109/ICDMW60847.2023.00139

M3 - Paper

SP - 1058

EP - 1064

T2 - 2023 IEEE International Conference on Data Mining Workshops

Y2 - 4 December 2023 through 4 December 2023

ER -

ID: 116882486