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. Petr Šild
- Ing. Evelyn Toseafa
Externí spolupracovníci:
- prof. Ing. Vladimír Olej, CSc.
- Ing. Aliaksandr Barushka, Ph.D.
- prof. Roberto Henriques (NOVA IMS, Universidade Nova de Lisboa)
- prof. Jean-Michel Sahut (IDRAC Business School)
Výstupy:
- 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.
- Hajek, P., Barushka, A., & Munk, M. (2020). Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining. Neural Computing and Applications, 32(23), 17259-17274.
- Papouskova, M., & Hajek, P. (2019). Two-stage consumer credit risk modelling using heterogeneous ensemble learning. Decision Support Systems, 118, 33-45.
- Hajek, P., & Henriques, R. (2017). Mining corporate annual reports for intelligent detection of financial statement fraud–A comparative study of machine learning methods. Knowledge-Based Systems, 128, 139-152.
