Supervised learning models to predict firm performance with annual reports: An empirical study
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- Georgia Boskou & Efstathios Kirkos & Charalambos Spathis, 2018. "Assessing Internal Audit with Text Mining," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-22, June.
- Dong Xu & Ruping Ge & Zhihua Niu, 2019. "Forward-Looking Element Recognition Based on the LSTM-CRF Model with the Integrity Algorithm," Future Internet, MDPI, vol. 11(1), pages 1-16, January.
- Luis Morales & José Aguilar & Danilo Chávez & Claudia Isaza, 2020. "LAMDA-HAD, an Extension to the LAMDA Classifier in the Context of Supervised Learning," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 283-316, January.
- Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
- Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
- Gaizka Garechana & Rosa Río-Belver & Iñaki Bildosola & Marisela Rodríguez Salvador, 2017. "Effects of innovation management system standardization on firms: evidence from text mining annual reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1987-1999, June.
- Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
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