@inproceedings{0c7791db467440dc999400cdbd1ca26e,
title = "Mining unstructured processes: An exploratory study on a distance learning domain",
abstract = "Modern techniques widely applied in data mining, including computational intelligence and machine learning, have been fairly neglected in process mining. We conducted an exploratory study to use artificial neural networks to extract knowledge from an unstructured process in the distance learning domain. We discuss some possible benefits and limitations regarding the mining of unstructured processes. Results suggest that applying either classical process mining or modern data mining techniques would result in significant benefits for this domain. Our work helps to guide new studies related to the application of modern mining techniques in process mining.",
author = "Maita, \{Ana R.C.\} and Marcelo Fantinato and Peres, \{Sarajane M.\} and Thom, \{Lucineia H.\} and Hung, \{Patrick C.K.\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Joint Conference on Neural Networks, IJCNN 2017 ; Conference date: 14-05-2017 Through 19-05-2017",
year = "2017",
month = jun,
day = "30",
doi = "10.1109/IJCNN.2017.7966261",
language = "English",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3240--3247",
booktitle = "2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings",
}