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Predicting financial distress using multimodal data: An attentive and regularized deep learning method
Information Processing and Management, Volume: 61, Issue: 4, Start page: 103703
Swansea University Author: Mohammad Abedin
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DOI (Published version): 10.1016/j.ipm.2024.103703
Abstract
Predicting financial distress using multimodal data: An attentive and regularized deep learning method
Published in: | Information Processing and Management |
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ISSN: | 0306-4573 |
Published: |
Elsevier BV
2024
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa65837 |
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Keywords: |
Financial distress prediction; Multimodal data; Deep learning; Attention mechanism; Conditional entropy |
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College: |
Faculty of Humanities and Social Sciences |
Funders: |
This work was supported by the National Natural Science Foundation of China (grants 72271073 and 72101073), and the University Synergy Innovation Program of Anhui Province (grant GXXT-2023-063). |
Issue: |
4 |
Start Page: |
103703 |