Process mining: a recent framework for extracting a model from event logs

Business Process Management (BPM) is a well-known discipline, with roots in previous theories related with optimizing management and improving businesses results. One can trace BPM back to the beginning of this century, although it was in more recent years when it gained a special focus of attention...

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Detalhes bibliográficos
Autor principal: Santos, Luís (author)
Formato: conferencePaper
Idioma:por
Publicado em: 2017
Assuntos:
Texto completo:https://hdl.handle.net/1822/81346
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/81346
Descrição
Resumo:Business Process Management (BPM) is a well-known discipline, with roots in previous theories related with optimizing management and improving businesses results. One can trace BPM back to the beginning of this century, although it was in more recent years when it gained a special focus of attention. Usually, traditional BPM approaches start from top and analyse the organization according some known rules from its structure or from the type of business. Process Mining (PM) is a completely different approach, since it aims to extract knowledge from event logs, which are widely present in many of today’s organizations. PM uses specialized data-mining algorithms, trying to uncover patterns and trends in these logs, and it is an alternative approach where formal process specification is not easily obtainable or is not cost-effective. This paper makes a literature review of major works issued about this theme.