Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Exploiting higher-order dependencies for process analytics

Exploiting higher-order dependencies for process analytics The purpose of this paper is to present a methodology to reveal complex events structures in events’ occurrences by analyzing event databases, targeting to systematizing events’ analysis and surpassing the need for idiographic approaches.Design/methodology/approachA process-oriented point of view is enabled by purposeful data transformations, and higher-order dependencies are discovered and exploited to capture the flows among the events.FindingsPolitical events do not follow a linear movement that is implied by a sequence, but they occur in varying patterns that cannot be reflected accurately when assuming only first-order dependencies.Originality/valueThe methodology suggests a novel way to look and to analyze raw event data and it offers an accessible, practicable and supplementary tool as it does not disturb any of the established relevant research designs, and it does not require any additional data to be applied. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Exploiting higher-order dependencies for process analytics

Kybernetes , Volume 49 (4): 14 – Apr 8, 2020

Loading next page...
 
/lp/emerald-publishing/exploiting-higher-order-dependencies-for-process-analytics-gczDVG72XZ
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0368-492X
DOI
10.1108/k-09-2018-0500
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to present a methodology to reveal complex events structures in events’ occurrences by analyzing event databases, targeting to systematizing events’ analysis and surpassing the need for idiographic approaches.Design/methodology/approachA process-oriented point of view is enabled by purposeful data transformations, and higher-order dependencies are discovered and exploited to capture the flows among the events.FindingsPolitical events do not follow a linear movement that is implied by a sequence, but they occur in varying patterns that cannot be reflected accurately when assuming only first-order dependencies.Originality/valueThe methodology suggests a novel way to look and to analyze raw event data and it offers an accessible, practicable and supplementary tool as it does not disturb any of the established relevant research designs, and it does not require any additional data to be applied.

Journal

KybernetesEmerald Publishing

Published: Apr 8, 2020

Keywords: Process analytics; Event analysis; Greece’s referendum; Higher-order networks

References