{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T21:34:10Z","timestamp":1787607250088,"version":"build-2736575974"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Technical Field Fund of Basic Research Strengthening Program","award":["Project no. 2021-JCJQJJ-0003"],"award-info":[{"award-number":["Project no. 2021-JCJQJJ-0003"]}]},{"name":"Doctoral Student Scientific Research Innovation Fund of Harbin Engineering University","award":["No. XK2090021030"],"award-info":[{"award-number":["No. XK2090021030"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 72361014"],"award-info":[{"award-number":["No. 72361014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Oper Res"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s10479-025-06612-w","type":"journal-article","created":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T02:57:50Z","timestamp":1746413870000},"page":"309-346","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Efficient multimodal learning for corporate credit risk prediction with an extended deep belief network"],"prefix":"10.1007","volume":"361","author":[{"given":"Sichong","family":"Lu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8035-4938","authenticated-orcid":false,"given":"Lean","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,5]]},"reference":[{"issue":"1","key":"6612_CR1","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1007\/s11263-016-0966-6","volume":"123","author":"A Agrawal","year":"2017","unstructured":"Agrawal, A., Lu, J., Antol, S., Mitchell, M., Zitnick, C. L., Parikh, D., & Batra, D. (2017). VQA: Visual question answering. International Journal of Computer Vision, 123(1), 4\u201331. https:\/\/doi.org\/10.1007\/s11263-016-0966-6","journal-title":"International Journal of Computer Vision"},{"issue":"4","key":"6612_CR2","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1111\/j.1540-6261.1968.tb00843.x","volume":"23","author":"EI Altman","year":"1968","unstructured":"Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589\u2013609. https:\/\/doi.org\/10.1111\/j.1540-6261.1968.tb00843.x","journal-title":"The Journal of Finance"},{"issue":"2","key":"6612_CR3","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1109\/TPAMI.2018.2798607","volume":"41","author":"T Baltru\u0161aitis","year":"2018","unstructured":"Baltru\u0161aitis, T., Ahuja, C., & Morency, L.-P. (2018). Multimodal machine learning: A survey and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(2), 423\u2013443. https:\/\/doi.org\/10.1109\/TPAMI.2018.2798607","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"6612_CR4","doi-asserted-by":"publisher","unstructured":"Bhargava, P., Drozd, A., & Rogers, A. (2021). Generalization in NLI: Ways (not) to go beyond simple heuristics. In Proceedings of the second workshop on insights from negative results in NLP (pp. 125\u2013135). https:\/\/doi.org\/10.18653\/v1\/2021.insights-1.18","DOI":"10.18653\/v1\/2021.insights-1.18"},{"key":"6612_CR5","unstructured":"Cavnar, W.\u00a0B., Trenkle, J.\u00a0M. (1994). N-gram-based text categorization. In Annual symposium on document analysis and information retrieval (vol. 161175, pp. 1\u20134). https:\/\/dsacl3-2019.github.io\/materials\/CavnarTrenkle.pdf"},{"issue":"2","key":"6612_CR6","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1108\/DTA-08-2019-0127","volume":"54","author":"J Choi","year":"2020","unstructured":"Choi, J., Suh, Y., & Jung, N. (2020). Predicting corporate credit rating based on qualitative information of MD &A transformed using document vectorization techniques. Data Technologies and Applications, 54(2), 151\u2013168. https:\/\/doi.org\/10.1108\/DTA-08-2019-0127","journal-title":"Data Technologies and Applications"},{"key":"6612_CR7","doi-asserted-by":"publisher","first-page":"113421","DOI":"10.1016\/j.dss.2020.113421","volume":"139","author":"P Craja","year":"2020","unstructured":"Craja, P., Kim, A., & Lessmann, S. (2020). Deep learning for detecting financial statement fraud. Decision Support Systems, 139, 113421. https:\/\/doi.org\/10.1016\/j.dss.2020.113421","journal-title":"Decision Support Systems"},{"issue":"6","key":"6612_CR8","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","volume":"41","author":"S Deerwester","year":"1990","unstructured":"Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391\u2013407. https:\/\/doi.org\/10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","journal-title":"Journal of the American Society for Information Science"},{"key":"6612_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5555\/1248547.1248548","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J. (2006). Statistical comparisons of classifiers over multiple data sets. The Journal of Machine Learning Research, 7, 1\u201330. https:\/\/doi.org\/10.5555\/1248547.1248548","journal-title":"The Journal of Machine Learning Research"},{"key":"6612_CR10","doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. In Annual conference of the North American chapter of the association for computational linguistics (vol. 1, pp. 4171\u20134186). https:\/\/doi.org\/10.18653\/V1\/N19-1423","DOI":"10.18653\/V1\/N19-1423"},{"key":"6612_CR11","doi-asserted-by":"publisher","unstructured":"El-Awady, K. (2021). Applicability of large corporate credit models to small business risk assessment. arXiv preprint arXiv:2201.08276. https:\/\/doi.org\/10.48550\/arXiv.2201.08276","DOI":"10.48550\/arXiv.2201.08276"},{"key":"6612_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-022-04766-5","author":"M Elhoseny","year":"2022","unstructured":"Elhoseny, M., Metawa, N., Sztano, G., & El-hasnony, I. M. (2022). Deep learning-based model for financial distress prediction. Annals of Operations Research. https:\/\/doi.org\/10.1007\/s10479-022-04766-5","journal-title":"Annals of Operations Research"},{"issue":"7","key":"6612_CR13","doi-asserted-by":"publisher","first-page":"1553","DOI":"10.1109\/TMM.2013.2267205","volume":"15","author":"G Evangelopoulos","year":"2013","unstructured":"Evangelopoulos, G., Zlatintsi, A., Potamianos, A., Maragos, P., Rapantzikos, K., Skoumas, G., & Avrithis, Y. (2013). Multimodal saliency and fusion for movie summarization based on aural, visual, and textual attention. IEEE Transactions on Multimedia, 15(7), 1553\u20131568. https:\/\/doi.org\/10.1109\/TMM.2013.2267205","journal-title":"IEEE Transactions on Multimedia"},{"key":"6612_CR14","doi-asserted-by":"publisher","unstructured":"Fan, A., & Palaniswami, M. (2000). Selecting bankruptcy predictors using a support vector machine approach. In Proceedings of the international joint conference on neural networks (vol. 6, pp. 354\u2013359). https:\/\/doi.org\/10.1109\/IJCNN.2000.859421","DOI":"10.1109\/IJCNN.2000.859421"},{"issue":"8","key":"6612_CR15","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1016\/j.patrec.2005.10.012","volume":"27","author":"T Fawcett","year":"2006","unstructured":"Fawcett, T. (2006). ROC graphs with instance-varying costs. Pattern Recognition Letters, 27(8), 882\u2013891. https:\/\/doi.org\/10.1016\/j.patrec.2005.10.012","journal-title":"Pattern Recognition Letters"},{"issue":"18","key":"6612_CR16","doi-asserted-by":"publisher","first-page":"7285","DOI":"10.1016\/j.eswa.2013.07.032","volume":"40","author":"E Fedorova","year":"2013","unstructured":"Fedorova, E., Gilenko, E., & Dovzhenko, S. (2013). Bankruptcy prediction for Russian companies: Application of combined classifiers. Expert Systems with Applications, 40(18), 7285\u20137293. https:\/\/doi.org\/10.1016\/j.eswa.2013.07.032","journal-title":"Expert Systems with Applications"},{"key":"6612_CR17","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.5555\/944919.944974","volume":"3","author":"G Forman","year":"2003","unstructured":"Forman, G. (2003). An extensive empirical study of feature selection metrics for text classification. Journal of Machine Learning Research, 3, 1289\u20131305. https:\/\/doi.org\/10.5555\/944919.944974","journal-title":"Journal of Machine Learning Research"},{"key":"6612_CR18","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.jnca.2017.10.011","volume":"103","author":"K Gai","year":"2018","unstructured":"Gai, K., Qiu, M., & Sun, X. (2018). A survey on FinTech. Journal of Network and Computer Applications, 103, 262\u2013273. https:\/\/doi.org\/10.1016\/j.jnca.2017.10.011","journal-title":"Journal of Network and Computer Applications"},{"key":"6612_CR19","doi-asserted-by":"publisher","unstructured":"Gao, H., Mao, J., Zhou, J., Huang, Z., Wang, L., & Xu, W. (2015). Are you talking to a machine? Dataset and methods for multilingual image question answering. In Advances in neural information processing systems (vol. 2, pp. 2296\u20132304). https:\/\/doi.org\/10.48550\/arXiv.1505.05612","DOI":"10.48550\/arXiv.1505.05612"},{"key":"6612_CR20","doi-asserted-by":"publisher","unstructured":"Glodek, M., Tschechne, S., Layher, G., Schels, M., Brosch, T., Scherer, S., K\u00e4chele, M., Schmidt, M., Neumann, H., Palm, G., & Schwenker, F. (2011). Multiple classifier systems for the classification of audio-visual emotional states. In Lecture notes in computer science (vol. 6975, pp. 359\u2013368). https:\/\/doi.org\/10.1007\/978-3-642-24571-8_47","DOI":"10.1007\/978-3-642-24571-8_47"},{"key":"6612_CR21","doi-asserted-by":"publisher","unstructured":"Hajek, P., Olej, V., & Prochazka, O. (2017). Predicting corporate credit ratings using content analysis of annual reports\u2014A Na\u00efve Bayesian network approach. In Enterprise applications, markets and services in the finance industry (pp. 47\u201361). https:\/\/doi.org\/10.1007\/978-3-319-52764-2_4","DOI":"10.1007\/978-3-319-52764-2_4"},{"key":"6612_CR22","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In IEEE conference on computer vision and pattern recognition, volume 2016-December (pp. 770\u2013778). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"issue":"8","key":"6612_CR23","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1162\/089976602760128018","volume":"14","author":"GE Hinton","year":"2002","unstructured":"Hinton, G. E. (2002). Training products of experts by minimizing contrastive divergence. Neural Computation, 14(8), 1771\u20131800. https:\/\/doi.org\/10.1162\/089976602760128018","journal-title":"Neural Computation"},{"issue":"5786","key":"6612_CR24","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton, G. E., & Salakhutdinov, R. R. (2006). Reducing the dimensionality of data with neural networks. Science, 313(5786), 504\u2013507. https:\/\/doi.org\/10.1126\/science.1127647","journal-title":"Science"},{"key":"6612_CR25","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/j.eswa.2018.09.039","volume":"117","author":"T Hosaka","year":"2019","unstructured":"Hosaka, T. (2019). Bankruptcy prediction using imaged financial ratios and convolutional neural networks. Expert Systems with Applications, 117, 287\u2013299. https:\/\/doi.org\/10.1016\/j.eswa.2018.09.039","journal-title":"Expert Systems with Applications"},{"issue":"1\u20132","key":"6612_CR26","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/s10479-022-04633-3","volume":"330","author":"B Huang","year":"2023","unstructured":"Huang, B., Yao, X., Luo, Y., & Li, J. (2023). Improving financial distress prediction using textual sentiment of annual reports. Annals of Operations Research, 330(1\u20132), 457\u2013484. https:\/\/doi.org\/10.1007\/s10479-022-04633-3","journal-title":"Annals of Operations Research"},{"issue":"5","key":"6612_CR27","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1016\/S0929-1199(03)00046-4","volume":"10","author":"LF Klapper","year":"2004","unstructured":"Klapper, L. F., & Love, I. (2004). Corporate governance, investor protection, and performance in emerging markets. Journal of Corporate Finance, 10(5), 703\u2013728. https:\/\/doi.org\/10.1016\/S0929-1199(03)00046-4","journal-title":"Journal of Corporate Finance"},{"key":"6612_CR28","doi-asserted-by":"publisher","first-page":"102155","DOI":"10.1016\/j.ribaf.2023.102155","volume":"67","author":"Z Li","year":"2024","unstructured":"Li, Z., Liang, S., Pan, X., & Pang, M. (2024). Credit risk prediction based on loan profit: Evidence from Chinese SMEs. Research in International Business and Finance, 67, 102155. https:\/\/doi.org\/10.1016\/j.ribaf.2023.102155","journal-title":"Research in International Business and Finance"},{"issue":"2","key":"6612_CR29","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.ejor.2016.01.012","volume":"252","author":"D Liang","year":"2016","unstructured":"Liang, D., Lu, C.-C., Tsai, C.-F., & Shih, G.-A. (2016). Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study. European Journal of Operational Research, 252(2), 561\u2013572. https:\/\/doi.org\/10.1016\/j.ejor.2016.01.012","journal-title":"European Journal of Operational Research"},{"key":"6612_CR30","doi-asserted-by":"publisher","unstructured":"Liu, W., Zhang, C., Yu, B., & Li, Y. (2019). A general multi-source data fusion framework. In International conference on machine learning and computing, volume part F148150 (pp. 285\u2013289). https:\/\/doi.org\/10.1145\/3318299.3318394","DOI":"10.1145\/3318299.3318394"},{"issue":"2","key":"6612_CR31","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1016\/j.ejor.2018.10.024","volume":"274","author":"F Mai","year":"2019","unstructured":"Mai, F., Tian, S., Lee, C., & Ma, L. (2019). Deep learning models for bankruptcy prediction using textual disclosures. European Journal of Operational Research, 274(2), 743\u2013758. https:\/\/doi.org\/10.1016\/j.ejor.2018.10.024","journal-title":"European Journal of Operational Research"},{"key":"6612_CR32","doi-asserted-by":"publisher","unstructured":"Mai, S., Hu, H., & Xing, S. (2020). Modality to modality translation: An adversarial representation learning and graph fusion network for multimodal fusion. In AAAI conference on artificial intelligence (vol. 34, pp. 164\u2013172). https:\/\/doi.org\/10.1609\/aaai.v34i01.5347","DOI":"10.1609\/aaai.v34i01.5347"},{"key":"6612_CR33","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.4163283","author":"R Makwana","year":"2022","unstructured":"Makwana, R., Bhatt, D., Delwadia, K., Shah, A., & Chaudhury, B. (2022). How to get investment grade rating in the age of explainable AI? SSRN Electronic Journal. https:\/\/doi.org\/10.2139\/ssrn.4163283","journal-title":"SSRN Electronic Journal"},{"issue":"3","key":"6612_CR34","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1080\/20954816.2022.2095749","volume":"10","author":"K Maria-Eleni","year":"2022","unstructured":"Maria-Eleni, K., Agoraki, G. P. K., & Laopodis, N. T. (2022). Geopolitical risks, uncertainty, and stock market performance. Economic and Political Studies, 10(3), 253\u2013265. https:\/\/doi.org\/10.1080\/20954816.2022.2095749","journal-title":"Economic and Political Studies"},{"key":"6612_CR35","doi-asserted-by":"publisher","unstructured":"Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. In International conference on learning representations. https:\/\/doi.org\/10.48550\/arXiv.1301.3781","DOI":"10.48550\/arXiv.1301.3781"},{"key":"6612_CR36","doi-asserted-by":"publisher","unstructured":"Morvant, E., Habrard, A., & Ayache, S. (2014). Majority vote of diverse classifiers for late fusion. In Structural, syntactic, and statistical pattern recognition (vol. 8621, pp. 153\u2013162). https:\/\/doi.org\/10.1007\/978-3-662-44415-3_16","DOI":"10.1007\/978-3-662-44415-3_16"},{"key":"6612_CR37","doi-asserted-by":"publisher","unstructured":"Mroueh, Y., Marcheret, E., & Goel, V. (2015). Deep multimodal learning for audio-visual speech recognition. In IEEE international conference on acoustics, speech and signal processing, volume 2015-August (pp. 2130\u20132134).https:\/\/doi.org\/10.1109\/ICASSP.2015.7178347","DOI":"10.1109\/ICASSP.2015.7178347"},{"key":"6612_CR38","doi-asserted-by":"publisher","unstructured":"Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., & Ng, A.\u00a0Y. (2011). Multimodal deep learning. In International conference on machine learning (pp. 689\u2013696). https:\/\/doi.org\/10.5555\/3104482.3104569","DOI":"10.5555\/3104482.3104569"},{"key":"6612_CR39","doi-asserted-by":"publisher","unstructured":"Nguyen, C.\u00a0V., Das, S.\u00a0R., He, J., Yue, S., Hanumaiah, V., Ragot, X., & Zhang, L. (2021). Multimodal machine learning for credit modeling. In Annual computers, software, and applications conference (pp. 1754\u20131759). https:\/\/doi.org\/10.1109\/COMPSAC51774.2021.00262","DOI":"10.1109\/COMPSAC51774.2021.00262"},{"key":"6612_CR40","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.amc.2014.02.028","volume":"234","author":"D Niklis","year":"2014","unstructured":"Niklis, D., Doumpos, M., & Zopounidis, C. (2014). Combining market and accounting-based models for credit scoring using a classification scheme based on support vector machines. Applied Mathematics and Computation, 234, 69\u201381. https:\/\/doi.org\/10.1016\/j.amc.2014.02.028","journal-title":"Applied Mathematics and Computation"},{"issue":"1","key":"6612_CR41","doi-asserted-by":"publisher","first-page":"109","DOI":"10.2307\/2490395","volume":"18","author":"JA Ohlson","year":"1980","unstructured":"Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109\u2013131. https:\/\/doi.org\/10.2307\/2490395","journal-title":"Journal of Accounting Research"},{"key":"6612_CR42","doi-asserted-by":"publisher","unstructured":"Ouyang, W., Chu, X., & Wang, X. (2014). Multi-source deep learning for human pose estimation. In IEEE computer society conference on computer vision and pattern recognition (pp. 2337\u20132344). https:\/\/doi.org\/10.1109\/CVPR.2014.299","DOI":"10.1109\/CVPR.2014.299"},{"issue":"9","key":"6612_CR43","doi-asserted-by":"publisher","first-page":"1306","DOI":"10.1109\/JPROC.2003.817150","volume":"91","author":"G Potamianos","year":"2003","unstructured":"Potamianos, G., Neti, C., Gravier, G., Garg, A., & Senior, A. W. (2003). Recent advances in the automatic recognition of audiovisual speech. Proceedings of the IEEE, 91(9), 1306\u20131325. https:\/\/doi.org\/10.1109\/JPROC.2003.817150","journal-title":"Proceedings of the IEEE"},{"issue":"6","key":"6612_CR44","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1109\/MSP.2017.2738401","volume":"34","author":"D Ramachandram","year":"2017","unstructured":"Ramachandram, D., & Taylor, G. W. (2017). Deep multimodal learning: A survey on recent advances and trends. IEEE Signal Processing Magazine, 34(6), 96\u2013108. https:\/\/doi.org\/10.1109\/MSP.2017.2738401","journal-title":"IEEE Signal Processing Magazine"},{"key":"6612_CR45","doi-asserted-by":"publisher","unstructured":"Ribeiro, M.\u00a0T., Singh, S., & Guestrin, C. (2016). \u201cWhy should I trust you?\u201d: Explaining the predictions of any classifier. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1135\u20131144). https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"issue":"1","key":"6612_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/505282.505283","volume":"34","author":"F Sebastiani","year":"2002","unstructured":"Sebastiani, F. (2002). Machine learning in automated text categorization. ACM Computing Surveys, 34(1), 1\u201347. https:\/\/doi.org\/10.1145\/505282.505283","journal-title":"ACM Computing Surveys"},{"key":"6612_CR47","doi-asserted-by":"publisher","DOI":"10.3390\/jrfm15010035","author":"S Shetty","year":"2022","unstructured":"Shetty, S., Musa, M., & Br\u00e9dart, X. (2022). Bankruptcy prediction using machine learning techniques. Journal of Risk and Financial Management. https:\/\/doi.org\/10.3390\/jrfm15010035","journal-title":"Journal of Risk and Financial Management"},{"key":"6612_CR48","doi-asserted-by":"publisher","unstructured":"Silberer, C., & Lapata, M. (2014). Learning grounded meaning representations with autoencoders. In Annual meeting of the association for computational linguistics (pp. 721\u2013732). https:\/\/doi.org\/10.3115\/v1\/P14-1068","DOI":"10.3115\/v1\/P14-1068"},{"key":"6612_CR49","unstructured":"Srivastava, N., & Salakhutdinov, R. (2012a). Learning representations for multimodal data with deep belief nets. In International conference on machine learning workshop. http:\/\/www.cs.toronto.edu\/~nitish\/icml2012\/paper.pdf"},{"key":"6612_CR50","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.5555\/2627435.2697059","volume":"3","author":"N Srivastava","year":"2012","unstructured":"Srivastava, N., & Salakhutdinov, R. (2012). Multimodal learning with deep Boltzmann machines. Advances in Neural Information Processing Systems, 3, 2222\u20132230. https:\/\/doi.org\/10.5555\/2627435.2697059","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"2","key":"6612_CR51","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.ejor.2021.03.008","volume":"295","author":"M Stevenson","year":"2021","unstructured":"Stevenson, M., Mues, C., & Bravo, C. (2021). The value of text for small business default prediction: A Deep Learning approach. European Journal of Operational Research, 295(2), 758\u2013771. https:\/\/doi.org\/10.1016\/j.ejor.2021.03.008","journal-title":"European Journal of Operational Research"},{"key":"6612_CR52","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.neucom.2014.11.086","volume":"176","author":"JA S\u00e1ez","year":"2016","unstructured":"S\u00e1ez, J. A., Luengo, J., & Herrera, F. (2016). Evaluating the classifier behavior with noisy data considering performance and robustness: The equalized loss of accuracy measure. Neurocomputing, 176, 26\u201335. https:\/\/doi.org\/10.1016\/j.neucom.2014.11.086","journal-title":"Neurocomputing"},{"issue":"1","key":"6612_CR53","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.ejor.2016.06.069","volume":"257","author":"M-F Tsai","year":"2017","unstructured":"Tsai, M.-F., & Wang, C.-J. (2017). On the risk prediction and analysis of soft information in finance reports. European Journal of Operational Research, 257(1), 243\u2013250. https:\/\/doi.org\/10.1016\/j.ejor.2016.06.069","journal-title":"European Journal of Operational Research"},{"key":"6612_CR54","doi-asserted-by":"publisher","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, \u0141., & Polosukhin, I. (2017). Attention is all you need. In Advances in neural information processing systems (vol. 30). https:\/\/doi.org\/10.48550\/arXiv.1706.03762","DOI":"10.48550\/arXiv.1706.03762"},{"key":"6612_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2022.113913","author":"G Wang","year":"2023","unstructured":"Wang, G., Ma, J., & Chen, G. (2023). Attentive statement fraud detection: Distinguishing multimodal financial data with fine-grained attention. Decision Support Systems. https:\/\/doi.org\/10.1016\/j.dss.2022.113913","journal-title":"Decision Support Systems"},{"key":"6612_CR56","doi-asserted-by":"publisher","unstructured":"Wu, Z., Jiang, Y.-G., Wang, J., Pu, J., & Xue, X. (2014). Exploring inter-feature and inter-class relationships with deep neural networks for video classification. In ACM conference on multimedia (pp. 167\u2013176). https:\/\/doi.org\/10.1145\/2647868.2654931","DOI":"10.1145\/2647868.2654931"},{"key":"6612_CR57","doi-asserted-by":"publisher","unstructured":"Yeh, S.-H., Wang, C.-J., & Tsai, M.-F. (2015). Deep belief networks for predicting corporate defaults. In 2015 24th wireless and optical communication conference (pp. 159\u2013163). https:\/\/doi.org\/10.1109\/WOCC.2015.7346197","DOI":"10.1109\/WOCC.2015.7346197"},{"issue":"4","key":"6612_CR58","doi-asserted-by":"publisher","first-page":"954","DOI":"10.1093\/biomet\/87.4.954","volume":"87","author":"I-K Yeo","year":"2000","unstructured":"Yeo, I.-K., & Johnson, R. A. (2000). A new family of power transformations to improve normality or symmetry. Biometrika, 87(4), 954\u2013959.","journal-title":"Biometrika"},{"key":"6612_CR59","doi-asserted-by":"publisher","DOI":"10.3390\/a9020041","author":"Y Yu","year":"2016","unstructured":"Yu, Y., Lin, H., Meng, J., & Zhao, Z. (2016). Visual and textual sentiment analysis of a microblog using deep convolutional neural networks. Algorithms. https:\/\/doi.org\/10.3390\/a9020041","journal-title":"Algorithms"},{"key":"6612_CR60","doi-asserted-by":"publisher","unstructured":"Zadeh, A., Chen, M., Cambria, E., Poria, S., & Morency, L.-P. (2017). Tensor fusion network for multimodal sentiment analysis. In Conference on empirical methods in natural language processing (pp. 1103\u20131114). https:\/\/doi.org\/10.18653\/v1\/D17-1115","DOI":"10.18653\/v1\/D17-1115"},{"key":"6612_CR61","doi-asserted-by":"publisher","unstructured":"Zadeh, A., Poria, S., Liang, P.\u00a0P., Cambria, E., Mazumder, N., & Morency, L.-P. (2018). Memory fusion network for multi-view sequential learning. In AAAI conference on artificial intelligence (vol. 32, pp. 5634\u20135641). https:\/\/doi.org\/10.1609\/aaai.v32i1.12021","DOI":"10.1609\/aaai.v32i1.12021"},{"key":"6612_CR62","doi-asserted-by":"publisher","first-page":"121484","DOI":"10.1016\/j.eswa.2023.121484","volume":"237","author":"X Zhang","year":"2024","unstructured":"Zhang, X., & Yu, L. (2024). Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods. Expert Systems with Applications, 237, 121484. https:\/\/doi.org\/10.1016\/j.eswa.2023.121484","journal-title":"Expert Systems with Applications"}],"container-title":["Annals of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-025-06612-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10479-025-06612-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-025-06612-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T12:58:51Z","timestamp":1779973131000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10479-025-06612-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,5]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["6612"],"URL":"https:\/\/doi.org\/10.1007\/s10479-025-06612-w","relation":{},"ISSN":["0254-5330","1572-9338"],"issn-type":[{"value":"0254-5330","type":"print"},{"value":"1572-9338","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,5]]},"assertion":[{"value":"30 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflicts of interest to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}