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Semi-supervised Learning Algorithm for Binary Relevance Multi-label Classification Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Analysis of Event Logs: Behavioral Graphs

Authors : Kateřina Slaninová, Dominik Vymětal, Jan Martinovič

Published in: Web Information Systems Engineering – WISE 2014 Workshops

Publisher: Springer International Publishing

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Abstract

Analysis of event logs is very important discipline used for the evaluation of performance and control-flow issues within the systems. This type of analysis is typically used in process mining sphere, where information systems, for example workflow management systems, enterprise resource planning systems, customer relationship management, supply chain management systems, and business to business systems record transactions and executed activities in a systematic way. Social network analysis takes part of process mining techniques, focused on activity performers, on users. The authors present a new approach to analysis of user behavior in the systems. The approach allows to find behavioral patterns and to find groups of users with similar behavior. An observer can obtain relations between the users on the basis of their similar behavior. The visualization of relations between the users is then presented by so called behavioral graphs. The approach was tested for event log analysis of a virtual company model developed as a multi-agent system by modeling environment MAREA.

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Footnotes
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Metadata
Title
Analysis of Event Logs: Behavioral Graphs
Authors
Kateřina Slaninová
Dominik Vymětal
Jan Martinovič
Copyright Year
2015
Book
Web Information Systems Engineering – WISE 2014 Workshops

Print ISBN: 978-3-319-20369-0

Electronic ISBN: 978-3-319-20370-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20370-6_4

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