Quotation Schönig, Stefan, Cabanillas Macias, Cristina, Di Ciccio, Claudio, Jablonski, Stefan, Mendling, Jan, Schönig, Stefan. 2018. Mining team compositions for collaborative work in business processes. Software & Systems Modeling (Springer). 17 (2), 675-693.


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Abstract

Process mining aims at discovering processes by extracting knowledge about their different perspectives from event logs. The resource perspective (or organisational perspective) deals, among others, with the assignment of resources to process activities. Mining in relation to this perspective aims to extract rules on resource assignments for the process activities. Prior research in this area is limited by the assumption that only one resource is responsible for each process activity, and hence, collaborative activities are disregarded. In this paper, we leverage this assumption by developing a process mining approach that is able to discover team compositions for collaborative process activities from event logs. We evaluate our novel mining approach in terms of computational performance and practical applicability.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Software & Systems Modeling
Citation Index SCI
Language English
Title Mining team compositions for collaborative work in business processes
Volume 17
Number 2
Year 2018
Page from 675
Page to 693
Reviewed? Y
URL http://link.springer.com/article/10.1007%2Fs10270-016-0567-4
DOI http://dx.doi.org/10.1007/s10270-016-0567-4
Open Access N

Associations

People
Schönig, Stefan (Former researcher)
Cabanillas Macias, Cristina (Former researcher)
Di Ciccio, Claudio (Former researcher)
Mendling, Jan (Details)
External
Jablonski, Stefan (University of Bayreuth, Germany)
Schönig, Stefan (University of Bayreuth, Germany)
Organization
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
5306 Business data processing (Details)
5367 Management information systems (Details)
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