Extending business failure prediction models with textual website content using deep learning

DOI10.1016/j.ejor.2022.06.060OpenAlexW4283811805MaRDI QIDQ2106750

Jochen De Weerdt, Kristof Coussement, Philipp Borchert, Arno de Caigny

Publication date: 19 December 2022

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2022.06.060

zbMATH Keywords

NLPtext mininganalyticsdeep learningbusiness failure prediction

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Related Items

Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making ⋮ Machine learning in bank merger prediction: a text-based approach ⋮ Navigational guidance -- a deep learning approach

Uses Software

• word2vec
• XGBoost
• Adam
• Tensor2Tensor
• BERT
• SMOTE

Cites Work

• Unnamed Item
• Unnamed Item
• A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees
• Bankruptcy prediction using terminal failure processes
• Bankruptcy prediction in banks and firms via statistical and intelligent techniques -- a review
• Automatic dimensionality selection from the scree plot via the use of profile likelihood
• A survey of business failures with an emphasis on prediction methods and industrial applications
• Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis
• Deep learning with long short-term memory networks for financial market predictions
• Cost-sensitive business failure prediction when misclassification costs are uncertain: a heterogeneous ensemble selection approach