@inproceedings{f75e705a9a1043fa922ccc24780a052d,
title = "A Framework for the Multi-modal Analysis of Novel Behavior in Business Processes",
abstract = "Novelty detection refers to the task of finding observations that are new or unusual when compared to the {\textquoteleft}known{\textquoteright} behavior. Its practical and challenging nature has been proven in many application domains while in process mining field has very limited researched. In this paper we propose a framework for the multi-modal analysis of novel behavior in business processes. The framework exploits the potential of representation learning, and allows to look at the process from different perspectives besides that of the control flow. Experiments on a real-world dataset confirm the quality of our proposal.",
keywords = "Multi-modality, Novelty detection, Process mining, Trace embedding",
author = "Antonino Rullo and Antonella Guzzo and Edoardo Serra and Erika Tirrito",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 ; Conference date: 04-11-2020 Through 06-11-2020",
year = "2020",
doi = "10.1007/978-3-030-62362-3_6",
language = "English",
isbn = "9783030623616",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "51--63",
editor = "Cesar Analide and Paulo Novais and David Camacho and Hujun Yin",
booktitle = "Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings",
address = "Germany",
}