@inproceedings{ghosh-etal-2021-finread,
title = "{F}in{R}ead: A Transfer Learning Based Tool to Assess Readability of Definitions of Financial Terms",
author = "Ghosh, Sohom and
Sengupta, Shovon and
Naskar, Sudip and
Singh, Sunny Kumar",
editor = "Bandyopadhyay, Sivaji and
Devi, Sobha Lalitha and
Bhattacharyya, Pushpak",
booktitle = "Proceedings of the 18th International Conference on Natural Language Processing (ICON)",
month = dec,
year = "2021",
address = "National Institute of Technology Silchar, Silchar, India",
publisher = "NLP Association of India (NLPAI)",
url = "https://aclanthology.org/2021.icon-main.81",
pages = "658--659",
abstract = "Simplified definitions of complex terms help learners to understand any content better. Comprehending readability is critical for the simplification of these contents. In most cases, the standard formula based readability measures do not hold good for measuring the complexity of definitions of financial terms. Furthermore, some of them works only for corpora of longer length which have at least 30 sentences. In this paper, we present a tool for evaluating readability of definitions of financial terms. It consists of a Light GBM based classification layer over sentence embeddings (Reimers et al., 2019) of FinBERT (Araci, 2019). It is trained on glossaries of several financial textbooks and definitions of various financial terms which are available on the web. The extensive evaluation shows that it outperforms the standard benchmarks by achieving a AU-ROC score of 0.993 on the validation set.",
}
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%0 Conference Proceedings
%T FinRead: A Transfer Learning Based Tool to Assess Readability of Definitions of Financial Terms
%A Ghosh, Sohom
%A Sengupta, Shovon
%A Naskar, Sudip
%A Singh, Sunny Kumar
%Y Bandyopadhyay, Sivaji
%Y Devi, Sobha Lalitha
%Y Bhattacharyya, Pushpak
%S Proceedings of the 18th International Conference on Natural Language Processing (ICON)
%D 2021
%8 December
%I NLP Association of India (NLPAI)
%C National Institute of Technology Silchar, Silchar, India
%F ghosh-etal-2021-finread
%X Simplified definitions of complex terms help learners to understand any content better. Comprehending readability is critical for the simplification of these contents. In most cases, the standard formula based readability measures do not hold good for measuring the complexity of definitions of financial terms. Furthermore, some of them works only for corpora of longer length which have at least 30 sentences. In this paper, we present a tool for evaluating readability of definitions of financial terms. It consists of a Light GBM based classification layer over sentence embeddings (Reimers et al., 2019) of FinBERT (Araci, 2019). It is trained on glossaries of several financial textbooks and definitions of various financial terms which are available on the web. The extensive evaluation shows that it outperforms the standard benchmarks by achieving a AU-ROC score of 0.993 on the validation set.
%U https://aclanthology.org/2021.icon-main.81
%P 658-659
Markdown (Informal)
[FinRead: A Transfer Learning Based Tool to Assess Readability of Definitions of Financial Terms](https://aclanthology.org/2021.icon-main.81) (Ghosh et al., ICON 2021)
ACL