Brief Overview of Selected Research Directions and Applications of Process Mining in KRaKEn Research Group
dc.contributor.author | Kluza, Krzysztof | |
dc.contributor.author | Zaremba, Mateusz | |
dc.contributor.author | Sepioło, Dominik | |
dc.contributor.author | Wiśniewski, Piotr | |
dc.contributor.author | Adrian, Weronika T. | |
dc.contributor.author | Gaudio, Maria Teresa | |
dc.contributor.author | Jemioło, Paweł | |
dc.contributor.author | Adrian, Marek | |
dc.contributor.author | Jobczyk, Krystian | |
dc.contributor.author | Ślażyński, Mateusz | |
dc.contributor.author | Stachuta-Terlecka, Bernadetta | |
dc.contributor.author | Ligęza, Antoni | |
dc.date.accessioned | 2023-09-21T11:58:09Z | |
dc.date.available | 2023-09-21T11:58:09Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Process mining allows for exploring processes using data from event logs. By providing insights into how processes are actually executed, rather than how they are supposed to be executed, process mining can be used for optimizing business processes and improving organizational efficiency. In this exploratory paper, we report on selected research threads related to process mining carried out within KRaKEn Research Group at AGH University of Science and Technology. We introduce a collection of initial ideas that require further exploration. Our research threads are concerned with the use of process mining techniques 1) for discovering processes from unstructured data, specifically text from e-mails, 2) for explaining black-box machine learning models, using process models as a global explanation, and 3) for analyzing data from different food industry systems to identify inefficiencies and provide recommendations for improvement. | en_EN |
dc.identifier.citation | Kluza K., Zaremba M., Sepioło D., Wiśniewski P., Adrian W.T., Gaudio M.T., Jemioło P., Adrian M., Jobczyk K., Ślażyński M., Stachura-Terlecka B., Ligęza A., Brief Overview of Selected Research Directions and Applications of Process Mining in KRaKEn Research Group. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 151-156, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.22. | |
dc.identifier.doi | 10.34658/9788366741928.22 | |
dc.identifier.isbn | 978-83-66741-92-8 | |
dc.identifier.uri | http://hdl.handle.net/11652/4798 | |
dc.identifier.uri | https://doi.org/10.34658/9788366741928.22 | |
dc.language.iso | en | en_EN |
dc.page.number | s. 151-156 | |
dc.publisher | Wydawnictwo Politechniki Łódzkiej | pl_PL |
dc.publisher | Lodz University of Technology Press | en_EN |
dc.relation.ispartof | Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928. | |
dc.rights | Dla wszystkich w zakresie dozwolonego użytku | pl_PL |
dc.rights | Fair use condition | en_EN |
dc.rights.license | Licencja PŁ | pl_PL |
dc.rights.license | LUT License | en_EN |
dc.subject | process mining | en_EN |
dc.subject | explainability | en_EN |
dc.subject | knowledge engineering | en_EN |
dc.subject | eksploracja procesów | pl_PL |
dc.subject | wyjaśnialność | pl_PL |
dc.subject | inżynieria wiedzy | pl_PL |
dc.title | Brief Overview of Selected Research Directions and Applications of Process Mining in KRaKEn Research Group | en_EN |
dc.type | Rozdział - monografia | pl_PL |
dc.type | Chapter - monograph | en_EN |