research-article

Translating Process Mining Results into Intelligible Business Information

Authors:

Paolo Ceravolo,

Antonia Azzini,

Ernesto Damiani,

Mariangela Lazoi,

Angelo CoralloAuthors Info & Claims

KMO '16: Proceedings of the The 11th International Knowledge Management in Organizations Conference on The changing face of Knowledge Management Impacting Society

Article No.: 14, Pages 1 - 8

https://doi.org/10.1145/2925995.2925997

Published: 25 July 2016 Publication History

Abstract

Most business processes are today rooted into an information system recording operational events in log files. Process Mining algorithms exploit this information to discover and qualify differences between observed and modelled process. However, the output of these algorithms are not clearly connected with business properties. Our work faces these limitations by proposing an approach for calibrating Process Mining results based on the Business Rules adopted by an organisation. The general idea relates on applying Process Mining algorithms on subsequent refinements of the event log, filtering process executions based on Business Rules. This way we are able to associate these results with specific characterisations of the process, as entailed by the corresponding Business Rules. This approach is confronted to a real world scenario using data provided by an Italian manufacturing company.

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Cited By

Andreswari RFauzi RValensia LChanifah S(2022)Conformance Analysis of Student Activities to Evaluate Implementation of Outcome-Based Education in Early of Pandemic using Process MiningSHS Web of Conferences10.1051/shsconf/202213903018139(03018)Online publication date: 13-May-2022
https://doi.org/10.1051/shsconf/202213903018
Latino MMenegoli MDe Giovanni M(2021)Evaluating the Sustainability Dimensions in the Food Supply Chain: Literature Review and Research RoutesSustainability10.3390/su13211181613:21(11816)Online publication date: 26-Oct-2021
https://doi.org/10.3390/su132111816
Okoye K(2020)Measuring the Impact of the Semantic-Based Process Mining ApproachApplications and Developments in Semantic Process Mining10.4018/978-1-7998-2668-2.ch008(217-237)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2668-2.ch008
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cover image ACM Other conferences

KMO '16: Proceedings of the The 11th International Knowledge Management in Organizations Conference on The changing face of Knowledge Management Impacting Society

July 2016

339 pages

ISBN:9781450340649

DOI:10.1145/2925995

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 July 2016

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KMO '16

KMO '16: The 11th International Knowledge Management in Organizations Conference

July 25 - 28, 2016

Hagen, Germany

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KMO '16 Paper Acceptance Rate 47 of 96 submissions, 49%;

Overall Acceptance Rate 47 of 96 submissions, 49%

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Cited By

Andreswari RFauzi RValensia LChanifah S(2022)Conformance Analysis of Student Activities to Evaluate Implementation of Outcome-Based Education in Early of Pandemic using Process MiningSHS Web of Conferences10.1051/shsconf/202213903018139(03018)Online publication date: 13-May-2022
https://doi.org/10.1051/shsconf/202213903018
Latino MMenegoli MDe Giovanni M(2021)Evaluating the Sustainability Dimensions in the Food Supply Chain: Literature Review and Research RoutesSustainability10.3390/su13211181613:21(11816)Online publication date: 26-Oct-2021
https://doi.org/10.3390/su132111816
Okoye K(2020)Measuring the Impact of the Semantic-Based Process Mining ApproachApplications and Developments in Semantic Process Mining10.4018/978-1-7998-2668-2.ch008(217-237)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2668-2.ch008
Marra MQuarta LRimini A(2020)A Processes Engineering Initiative for Lean Performing Arts OrganizationsProceedings of the 6th European Lean Educator Conference10.1007/978-3-030-41429-0_35(351-361)Online publication date: 5-May-2020
https://doi.org/10.1007/978-3-030-41429-0_35
Corallo ALazoi MStriani F(2020)Process mining and industrial applications: A systematic literature reviewKnowledge and Process Management10.1002/kpm.163027:3(225-233)Online publication date: 26-Feb-2020
https://doi.org/10.1002/kpm.1630
Garcia CMeincheim AFaria Junior EDallagassa MSato DCarvalho DSantos EScalabrin E(2019)Process mining techniques and applications – A systematic mapping studyExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.05.003133:C(260-295)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1016/j.eswa.2019.05.003
Leida MCeravolo PDamiani EAsal RColombo M(2019)Dynamic Access Control to Semantics-Aware Streamed Process LogsJournal on Data Semantics10.1007/s13740-019-00106-2Online publication date: 24-Jul-2019
https://doi.org/10.1007/s13740-019-00106-2
Pika ALeyer MWynn MFidge CHofstede AAalst W(2017)Mining Resource Profiles from Event LogsACM Transactions on Management Information Systems10.1145/30412188:1(1-30)Online publication date: 23-Mar-2017
https://dl.acm.org/doi/10.1145/3041218
Ceravolo PDamiani ETorabi MBarbon S(2017)Toward a New Generation of Log Pre-processing Methods for Process MiningBusiness Process Management Forum10.1007/978-3-319-65015-9_4(55-70)Online publication date: 3-Aug-2017
https://doi.org/10.1007/978-3-319-65015-9_4

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