prof. RNDr. Michal Munk, PhD.
- michal.munk@upce.cz
-
Centrum pro vědu a výzkum (40590)
Fakulta ekonomicko-správní
Profesor
- Výuka, rozvrh, termíny
- Publikace
- Projekty
Výuka
| FES/EPMMS (2023) | G PR - SE | |
| FES/ESMM (2023) | - PR - SE | |
| FES/HPMMS (2023) | G PR - SE | |
| FES/HSMM (2023) | - PR - SE |
Rozvrh
| 17. 05. 2024 | ||||
| 09:00-12:00 | EA / 05029 | FES | EPMMS | 2 |
| 09:00-12:00 | EA / 05029 | FES | ESMM | 5 |
| 09:00-12:00 | EA / 05029 | FES | HPMMS | 1 |
| 09:00-12:00 | EA / 05029 | FES | HSMM | 1 |
Termíny
Publikace
| HÁJEK, P. - MUNK, M. Speech emotion recognition and text sentiment analysis for financial distress prediction Neural Computing and Applications, 2023, vol. 35, no. 29, s. 21463-21477. ISSN: 0941-0643. | |
| FEDOROVA, Y. - PILKOVÁ, A. - MIKUŠ, J. - MUNK, M. - REHÁK, J. Emotional intelligence profiles and intergenerational collaboration in business Journal of Business Economics and Management, 2023, vol. 24, no. 4, s. 797-817. ISSN: 1611-1699. | |
| HALVONIK, D. - KAPUSTA, J. - MUNK, M. Improve estimated time-on-task calculation in a Virtual Learning Environment Interactive Learning Environments, 2023, vol. 31, no. 5, s. 2914 - 2929. ISSN: 1049-4820. | |
| SZABO NAGY, K. - KAPUSTA, J. - MUNK, M. Feature extraction from unstructured texts as a combination of the morphological and the syntactic analysis and its usage in fake news classification tasks Neural Computing and Applications, 2023, vol. 35, no. 29, s. 22055-22067. ISSN: 0941-0643. | |
| FORGAC, F. - MUNKOVA, D. - MUNK, M. - KELEBERCOVA, L. Evaluating automatic sentence alignment approaches on English-Slovak sentences Scientific Reports, 2023, vol. 13, no. 1, s. 20123. ISSN: 2045-2322. | |
| SUNNY, F. - HÁJEK, P. - MUNK, M. - ABEDIN, M. - SATU, M. - EFAT, M. - ISLAM, M. A Systematic Review of Blockchain Applications IEEE ACCESS, 2022, vol. 10, no. Neuveden, s. 59155-59177. ISSN: 2169-3536. | |
| FLORIS, N. - SCHWARCZ, P. - SCHWARCZOVA, L. - MUNK, M. Short Food Supply Chains and Small Farms-Evidence from Slovakia Sustainability, 2022, vol. 14, no. 5, s. 2728. ISSN: 2071-1050. | |
| PILKOVA, A. - MUNK, M. - BENKO, L. - BLAZEKOVA, P. - KAPUSTA, J. Pillar 3: Does banking regulation support stakeholders' interest in banks financial and risk profile? PLoS One, 2021, vol. 16, no. 10, s. e0258449. ISSN: 1932-6203. | |
| BENKOVA, L. - MUNKOVA, D. - BENKO, L. - MUNK, M. Evaluation of English-Slovak neural and statistical machine translation Applied Science - Basel, 2021, vol. 11, no. 7, s. 2948. ISSN: 2076-3417. | |
| KAPUSTA, J. - DRLIK, M. - MUNK, M. Using of n-grams from morphological tags for fake news classification PeerJ Computer Science, 2021, vol. 7, no. 19.7.2021, s. e624. ISSN: 2376-5992. | |
| MUNKOVA, D. - MUNK, M. - BENKO, L. - HÁJEK, P. The role of automated evaluation techniques in online professional translator training PeerJ Computer Science, 2021, vol. 7, no. 4.10.2021, s. e706. ISSN: 2376-5992. | |
| HÁJEK, P. - BARUSHKA, A. - MUNK, M. Neural networks with emotion associations, topic modeling and supervised term weighting for sentiment analysis International Journal of Neural Systems, 2021, vol. 31, no. 10, s. 2150013. ISSN: 0129-0657. | |
| DRLIK, M. - MUNK, M. - SKALKA, J. Identification of changes in VLE stakeholders' behavior over tme using frequent patterns mining IEEE ACCESS, 2021, vol. 9, no. 1.2.2021, s. 23795-23813. ISSN: 2169-3536. | |
| HÁJEK, P. - BARUSHKA, A. - MUNK, M. Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining Neural Computing and Applications, 2020, vol. 32, no. 23, s. 17259-17274. ISSN: 0941-0643. | |
| HÁJEK, P. - BARUSHKA, A. - MUNK, M. Opinion mining of consumer reviews using deep neural networks with word-sentiment associations. In IFIP Advances in Information and Communication Technology. Vol. 583. Heidelberg: Springer, 2020. s. 419-429 s. ISBN 978-3-030-49160-4. | |
| KAPUSTA, J. - MUNK, M. - SVEC, P. Selection of Suitable PageRank Calculation for Analysis of Differences Between Expected and Observed Probability of Accesses to Web Pages. In Multi-disciplinary Trends in Artificial Intelligence. Heidelberg: Springer, 2018. s. 139-150 s. ISBN 978-3-030-03013-1. |
Projekty
Aspektově orientovaná analýza sentimentu finančních textů pro predikci finanční výkonnosti podniku
01.01.22 - 31.12.24
Program: Standardní projekty
Poskytovatel: Grantová agentura ČR
Pozice na projektu: Spoluřešitel
01.01.22 - 31.12.24
Program: Standardní projekty
Poskytovatel: Grantová agentura ČR
Pozice na projektu: Spoluřešitel
