Predictive process monitoring using a markov model technique

Naveed Khan, Sally McClean, Zulfiqar Ali, Aftab Ali, Darryl Charles, Paul Taylor, Detlef Nauck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Information systems play a vital role in business process understanding through recording data where each process execution is represented in event logs. These event logs consist of a collection of traces which characterise the execution of a process. The techniques that analyse such types of data are broadly known as process mining. Hence, Process mining is a family of techniques to evaluate and analyse business process based on their pragmatic behaviour as recorded in event logs. Predictive process monitoring aims to predict how the completion of running process events can be anticipated. In this paper, Markov chain models have been investigated for prediction of future process events by considering a sequence of events. The Markov model is a special type of statistical (process) model that are used to evaluate systems where it is considered that future states depend only on the current state and not on previous states. Results have been evaluated using an accuracy metric for a dataset contains tasks from a ticketing management process of a software company.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019
EditorsMahdi H. Miraz, Peter S. Excell, Andrew Ware, Safeeullah Soomro, Maaruf Ali
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-196
Number of pages4
ISBN (Electronic)9781728121383
DOIs
Publication statusPublished - 26 Dec 2019
Externally publishedYes
Event2nd International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019 - London, United Kingdom
Duration: 22 Aug 201923 Aug 2019

Publication series

NameProceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019

Conference

Conference2nd International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019
CountryUnited Kingdom
CityLondon
Period22/08/201923/08/2019

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT This research is supported by the BTIIC (BT Ireland Innovation Centre) project, funded by BT and Invest Northern Ireland.

Publisher Copyright:
© 2019 IEEE.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Markov chain Model
  • Monitoring
  • Process analytic

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Optimization
  • Health Informatics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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