APD tool: Mining anomalous patterns from event logs

L. Genga, M. Alizadeh, D. Potena, C. Diamantini, Nicola Zannone

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)
97 Downloads (Pure)

Samenvatting

A main challenge of today's organizations is the monitoring of their processes to check whether these processes comply with process models specifying the prescribed behavior. Deviations from the prescribed behavior can represent either legitimate work practices not described by the models, which highlight the need of improving it to better reflect the reality, or malicious behaviors representing, for instance, security breaches and frauds. In this paper, we present a tool designed to extract anomalous patterns representing recurrent deviations, together with their correlations, from historical logging data. The tool is targeted to researchers and practitioners in business process and security domains, with background in process mining.

Originele taal-2Engels
TitelProceedings of the BPM Demo Track and BPM Dissertation Award
RedacteurenR. Clarisó, H. Leopold, J. Mendling, W. van der Aalst, A. Kumar, B. Pentland, M. Weske
UitgeverijSun SITE Central Europe
Aantal pagina's5
StatusGepubliceerd - 2017
Evenement15th International Conference on Business Process Management (BPM 2017) - Barcelona, Spanje
Duur: 10 sep. 201715 sep. 2017
Congresnummer: 15
https://bpm2017.cs.upc.edu/

Publicatie series

NaamCEUR workshop proceedings
Volume1920
ISSN van elektronische versie1613-0073

Congres

Congres15th International Conference on Business Process Management (BPM 2017)
Verkorte titelBPM 2017
Land/RegioSpanje
StadBarcelona
Periode10/09/1715/09/17
Internet adres

Vingerafdruk

Duik in de onderzoeksthema's van 'APD tool: Mining anomalous patterns from event logs'. Samen vormen ze een unieke vingerafdruk.

Citeer dit