A Framework for the Multi-Modal Analysis of Novel Behavior in Business Processes

Antonino Rullo, Antonella Guzzo, Edoardo Serra, Erika Tirrito

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Novelty detection refers to the task of finding observations that are new or unusual when compared to the ‘known’ 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.

Original languageAmerican English
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4-6, 2020, Proceedings
StatePublished - 1 Jan 2020

Keywords

  • multi-modality
  • novelty detection
  • process mining
  • trace embedding

EGS Disciplines

  • Computer Sciences

Fingerprint

Dive into the research topics of 'A Framework for the Multi-Modal Analysis of Novel Behavior in Business Processes'. Together they form a unique fingerprint.

Cite this