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A graph and trace clustering-based approach for abstracting mined business process podels

  • Process model discovery is a significant research topic in the business process mining area. However, existing workflow discovery techniques run into a stone wall while dealing with event logs generated from highly flexible environments because the raw models mined from such logs often suffer from the problem of inaccuracy and high complexity. In this paper, we propose a new process model abstraction technique for solving this problem. The proposed technique is able to optimise the quality of the potential high level model (abstraction model) so that a high-quality abstraction model can be acquired and also considers the quality of the submodels generated where each sub-model is employed to show the details of its relevant high level activity in the high level model.

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Metadaten
Author:Yaguang Sun, Bernhard BauerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1200422
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/120042
ISBN:978-989-758-187-8OPAC
Parent Title (English):Proceedings of the 18th International Conference on Enterprise Information Systems (ICEIS 2016), April 25-28, 2016, Rome, Italy, volume 1
Publisher:SciTePress
Place of publication:Setúbal
Editor:Slimane Hammoudi, Leszek Maciaszek, Michele M. Missikoff, Olivier Camp, José Cordeiro
Type:Conference Proceeding
Language:English
Year of first Publication:2016
Publishing Institution:Universität Augsburg
Release Date:2025/03/12
First Page:63
Last Page:74
DOI:https://doi.org/10.5220/0005833900630074
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik / Professur für Theorie verteilter Systeme
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)

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