Handling Big(ger) logs: Connecting ProM 6 to apache hadoop
Resumen: Within process mining the main goal is to support the analysis, im- provement and apprehension of business processes. Numerous process mining techniques have been developed with that purpose. The majority of these tech- niques use conventional computation models and do not apply novel scalable and distributed techniques. In this paper we present an integrative framework connect- ing the process mining framework ProM with the distributed computing environ- ment Apache Hadoop. The integration allows for the execution of MapReduce jobs on any Apache Hadoop cluster enabling practitioners and researchers to ex- plore and develop scalable and distributed process mining approaches. Thus, the new approach enables the application of different process mining techniques to events logs of several hundreds of gigabytes.
Idioma: Inglés
Año: 2015
Publicado en: CEUR Workshop Proceedings 1418 (2015), 80-84
ISSN: 1613-0073

Originalmente disponible en: Texto completo de la revista

Factor impacto SCIMAGO:

Financiación: info:eu-repo/grantAgreement/ES/DGA/87230-2
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2014-56633-C3-2-R
Tipo y forma: Article (Published version)
Área (Departamento): Lenguajes y Sistemas Informáticos (Departamento de Informática e Ingeniería de Sistemas)

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Articles > Artículos por área > Lenguajes y Sistemas Informáticos

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