Rule-Mining and Clustering in Business Process Analysis

Autor:	Stephanie Kiss, Paul N. Taylor
Rok vydání:	2018
Předmět:	Complex data type Computer science Process (engineering) Business process Business analysis Context (language use) Data mining Directed acyclic graph Cluster analysis computer.software_genre computer Domain (software engineering)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030041908 SGAI Conf.
DOI:	10.1007/978-3-030-04191-5_22
Popis:	The analysis of complex business processes is a challenging topic. Machine learning provides many tools to help with the analysis/understanding of complex data. In this paper we present the application of two types of technique to this domain. First, rule mining techniques to discover relationships between process behaviour and outcomes. Second, a technique presented is one suitable for clustering arbitrary length directed acyclic graphs such as those that represent business process executions. Both cases are presented in the context of a real business process.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::85ea83876d416d6c52efa48d4bcf7154 https://doi.org/10.1007/978-3-030-04191-5_22 Zobrazit plný text záznamu