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Using Natural Language Processing to Enhance Understandability of Financial Texts

Published: 04 January 2023 Publication History

Abstract

Dealing with money has always been one of the basic skills one needs to live a comfortable life. However, financial literacy rates across the nations are extremely low. Furthermore, over the years the returns from traditional investment avenues like bank fixed deposits (FD), real estate, etc. have been diminishing. This entices new-age investors to trade and reap profits from the ever-growing stock markets. Nevertheless, in reality, only a handful of active traders are able to earn more than the FD rates. This is due to the lack of financial knowledge. The presence of complex concepts and jargons further reduces comprehensibility. In this paper, we present how financial texts can be demystified using Natural Language Processing (NLP). It consists of neural-based readability assessment and hypernym extraction tools to improve the readability of financial texts. Other modules include financial domain specific systems for automated claim detection, sustainability assessment, etc.

References

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  • (2024)Demystifying Financial Texts Using Natural Language ProcessingProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680258(5451-5454)Online publication date: 21-Oct-2024

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CODS-COMAD '23: Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)
January 2023
357 pages
ISBN:9781450397971
DOI:10.1145/3570991
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 January 2023

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Author Tags

  1. claim detection
  2. financial text processing
  3. hypernym detection
  4. natural language processing
  5. readability

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CODS-COMAD 2023

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Overall Acceptance Rate 197 of 680 submissions, 29%

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Cited By

View all
  • (2024)Demystifying Financial Texts Using Natural Language ProcessingProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680258(5451-5454)Online publication date: 21-Oct-2024

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