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http://hdl.handle.net/1942/41894
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DC Field | Value | Language |
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dc.contributor.author | VAN HOUDT, Greg | - |
dc.contributor.author | de Leoni, Massimiliano | - |
dc.contributor.author | MARTIN, Niels | - |
dc.contributor.author | DEPAIRE, Benoit | - |
dc.date.accessioned | 2023-11-30T15:25:35Z | - |
dc.date.available | 2023-11-30T15:25:35Z | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2023-11-29T08:32:14Z | - |
dc.identifier.citation | INFORMATION SYSTEMS, 121 (Art N° 102320) | - |
dc.identifier.issn | 0306-4379 | - |
dc.identifier.uri | http://hdl.handle.net/1942/41894 | - |
dc.description.abstract | These days, businesses keep track of more and more data in their information systems. Moreover, this data becomes more fine-grained than ever, tracking clicks and mutations in databases at the lowest level possible. Faced with such data, process discovery often struggles with producing comprehensible models, as they instead return spaghetti-like models. Such finely granulated models do not fit the business user’s mental model of the process under investigation. To tackle this, event log abstraction (ELA) techniques can transform the underlying event log to a higher granularity level. However, insights into the performance of these techniques are lacking in literature as results are only based on small-scale experiments and are often inconclusive. Against this background, this paper evaluates state-of-the-art abstraction techniques on 400 event logs. Results show that ELA sacrifices fitness for precision, but complexity reductions heavily depend on the ELA technique used. This study also illustrates the importance of a larger-scale experiment, as sub-sampling of results leads to contradictory conclusions. | - |
dc.description.sponsorship | The resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government. The authors would like to express a special thanks to dr. ir. H.M.W. Verbeek (TU/e - Eindhoven University of Technology) for his assistance and troubleshooting in writing the ProM CLI plugins required to run our computations and dr. G.A.W.M. van Hulzen (UHasselt - Hasselt University) for the aid in configuring and optimizing the code on the VSC. So do we want to thank Claudia Fracca and the team at ESTECO S.p.A. for helping us generate the synthetic event logs used in the experiments using the L-Sim tool. This research is funded by the UHasselt BOF under grant number BOF19OWB19. The research work of prof. dr. M. de Leoni is partly supported by the Department of Mathematics, University of Padua, through the BIRD projects ‘‘Web-site Interaction Discovery’’ (code BIRD219730/21) and ‘‘Data-driven Business Process Improvement’’ (code BIRD215924/21). | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.rights | 2023 Elsevier Ltd. All rights reserved. | - |
dc.subject.other | Process mining | - |
dc.subject.other | Event log abstraction | - |
dc.subject.other | Unsupervised learning | - |
dc.subject.other | Comprehensibility | - |
dc.title | An empirical evaluation of unsupervised event log abstraction techniques in process mining | - |
dc.type | Journal Contribution | - |
dc.identifier.volume | 121 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Van Houdt, G (corresponding author), UHasselt Hasselt Univ, Res Grp Business Informat, Agoralaan, B-3590 Diepenbeek, Belgium. | - |
dc.description.notes | greg.vanhoudt@uhasselt.be | - |
local.publisher.place | THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.artnr | 102320 | - |
local.type.programme | VSC | - |
dc.identifier.doi | 10.1016/j.is.2023.102320 | - |
dc.identifier.isi | 001132094500001 | - |
local.provider.type | CrossRef | - |
local.description.affiliation | [Van Houdt, Greg; Martin, Niels; Depaire, Benoit] UHasselt Hasselt Univ, Res Grp Business Informat, Agoralaan, B-3590 Diepenbeek, Belgium. | - |
local.description.affiliation | [de Leoni, Massimiliano] Univ Padua, Dept Math, Via Trieste 63, I-35121 Padua, Italy. | - |
local.dataset.url | https://github.com/gregvanhoudt/Unsupervised-ELA-Framework | - |
local.uhasselt.international | yes | - |
item.embargoEndDate | 2024-09-01 | - |
item.fullcitation | VAN HOUDT, Greg; de Leoni, Massimiliano; MARTIN, Niels & DEPAIRE, Benoit (2024) An empirical evaluation of unsupervised event log abstraction techniques in process mining. In: INFORMATION SYSTEMS, 121 (Art N° 102320). | - |
item.contributor | VAN HOUDT, Greg | - |
item.contributor | de Leoni, Massimiliano | - |
item.contributor | MARTIN, Niels | - |
item.contributor | DEPAIRE, Benoit | - |
item.accessRights | Embargoed Access | - |
item.fulltext | With Fulltext | - |
crisitem.journal.issn | 0306-4379 | - |
crisitem.journal.eissn | 1873-6076 | - |
Appears in Collections: | Research publications |
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Published Version.pdf Restricted Access | Published version | 882.29 kB | Adobe PDF | View/Open Request a copy |
An_Empirical_Evaluation_of_Unsupervised_Event_Log_Abstraction_Techniques_in_Process_Mining__IS_.pdf Until 2024-09-01 | Peer-reviewed author version | 364.19 kB | Adobe PDF | View/Open Request a copy |
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