Detecting context-based in-claim numerals in Financial Earnings Conference Calls-Reference-Cited by-同舟云学术

Detecting context-based in-claim numerals in Financial Earnings Conference Calls

Published:2022-05-15 Issue:5 Volume:14 Page:2559-2566
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Ghosh Sohom^ORCID,Naskar Sudip Kumar^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-022-00952-7.pdf

Reference31 articles.

1. Aharoni E, Polnarov A, Laveen T, Hershcovich D, Levy R, Rinott R, Gutfreund D, Slonim N (2014) A benchmark dataset for automatic detection of claims and evidence in the context of controversial topics. In: Proceedings of the first workshop on argumentation mining, Baltimore, Maryland. Association for Computational Linguistics, pp 64–68. https://doi.org/10.3115/v1/W14-2109. https://aclanthology.org/W14-2109

2. Araci D (2019) Finbert: Financial sentiment analysis with pre-trained language models

3. Azzi AA, Bouamor H (2019) Fortia1@ the ntcir-14 finnum task: enriched sequence labeling for numeral classification. In: Proceedings of the 14th NTCIR conference on evaluation of information access technologies, pp 526–538. http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/02-NTCIR14-FINNUM-AzziA.pdf

4. Bar-Haim R, Edelstein L, Jochim C, Slonim N (2017) Improving claim stance classification with lexical knowledge expansion and context utilization. In: Proceedings of the 4th workshop on argument mining, Copenhagen, Denmark, Sept. Association for Computational Linguistics, pp 32–38. https://doi.org/10.18653/v1/W17-5104. https://aclanthology.org/W17-5104

5. Botnevik B, Sakariassen E, Setty V (2020) BRENDA: browser extension for fake news detection. Association for Computing Machinery, New York, pp 2117–2120. 10(1145/3397271):3401396

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