Výzkumné zaměření: výpočetní inteligence, strojové učení, datová věda, text mining, hluboké učení, fuzzy systémy.
Interní členové – akademici:
- prof. RNDr. Michal Munk, PhD.
- doc. Mgr. Ing. Martin Boďa, PhD.
Interní členové – doktorandi
- Abdelrahman Taha Youssef, M.Sc.
- Ing. Zeru Kifle Kebede
- Andew Asante, M.Sc.
Externí spolupracovníci:
- prof. Ing. Vladimír Olej, CSc.
- prof. Roberto Henriques (NOVA IMS, Universidade Nova de Lisboa)
- prof. Jean-Michel Sahut (IDRAC Business School)
Výstupy:
- Hajek, P., & Munk, M. (2024). Corporate financial distress prediction using the risk-related information content of annual reports. Information Processing & Management, 61(5), 103820.
- Hajek, P., & Henriques, R. (2024). Predicting M&A targets using news sentiment and topic detection. Technological Forecasting and Social Change, 201, 123270.
- Hajek, P., Hikkerova, L., & Sahut, J. M. (2023). Fake review detection in e-Commerce platforms using aspect-based sentiment analysis. Journal of Business Research, 167, 114143.
- Hajek, P., & Munk, M. (2023). Speech emotion recognition and text sentiment analysis for financial distress prediction. Neural Computing and Applications, 35(29), 21463-21477.
- Hajek, P., & Sahut, J. M. (2022). Mining behavioural and sentiment-dependent linguistic patterns from restaurant reviews for fake review detection. Technological Forecasting and Social Change, 177, 121532.
- Hajek, P., & Novotny, J. (2022). Fuzzy rule-based prediction of gold prices using news affect. Expert Systems with Applications, 193, 116487.
