Do You Behave Always the Same?: A Process Mining Approach

Gemma Di Federico; Andrea Burattin

doi:10.1007/978-3-031-27815-0_1

Do You Behave Always the Same? A Process Mining Approach

Gemma Di Federico^*
, Andrea Burattin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Human behavior could be represented in the form of a process. Existing process modeling notations, however, are not able to faithfully represent these very flexible and unstructured processes. Additionalnon-process aware perspectives should be considered in the representation. Control-flow and data dimensions should be combined to build arobust model which can be used for analysis purposes. The work in thispaper proposes a new hybrid model in which these dimensions are combined. An enriched conformance checking approach is described, basedon the alignment of imperative and declarative process models, whichalso supports data dimensions from a statistical viewpoint.

Original language	English
Title of host publication	Proceedings of Process Mining Workshop : ICPM 2022 International Workshops
Volume	468
Publisher	Springer
Publication date	2023
Pages	5-17
ISBN (Print)	978-3-031-27814-3
ISBN (Electronic)	978-3-031-27815-0
DOIs	https://doi.org/10.1007/978-3-031-27815-0_1
Publication status	Published - 2023
Event	4th International Conference on Process Mining - Bolzano, Italy Duration: 23 Oct 2022 → 28 Oct 2022 Conference number: 4 https://icpmconference.org/2022/

Conference

Conference	4th International Conference on Process Mining
Number	4
Country/Territory	Italy
City	Bolzano
Period	23/10/2022 → 28/10/2022
Internet address	https://icpmconference.org/2022/

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10.1007/978-3-031-27815-0_1Licence: CC BY

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Cite this

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title = "Do You Behave Always the Same?: A Process Mining Approach",

abstract = "Human behavior could be represented in the form of a process. Existing process modeling notations, however, are not able to faithfully represent these very flexible and unstructured processes. Additionalnon-process aware perspectives should be considered in the representation. Control-flow and data dimensions should be combined to build arobust model which can be used for analysis purposes. The work in thispaper proposes a new hybrid model in which these dimensions are combined. An enriched conformance checking approach is described, basedon the alignment of imperative and declarative process models, whichalso supports data dimensions from a statistical viewpoint.",

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DO - 10.1007/978-3-031-27815-0_1

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BT - Proceedings of Process Mining Workshop

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