Schönig, Stefan, Cabanillas Macias, Cristina, Di Ciccio, Claudio, Jablonski, Stefan, Mendling, Jan. 2016. Mining Resource Assignments and Teamwork Compositions from Process Logs. Softwaretechnik-Trends 36 (4), 1-6.

RIS

@ARTICLE{Schönig2016,
title = {Mining Resource Assignments and Teamwork Compositions from Process Logs},
author = {Stefan Schönig and Cristina Cabanillas Macias and Claudio Di Ciccio and Stefan Jablonski and Jan Mendling},
year = {2016},
doi = {n.a.},
url = {http://pi.informatik.uni-siegen.de/stt/36_4/./03_Technische_Beitraege/Schoenig_et_al_2016.pdf},
volume = {36},
number = {4},
language = {EN},
pages = {1-6},
journal = {Softwaretechnik-Trends},
abstract = {Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions. This is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they are not fully efficient; (iii) the discovered process models are difficult to read due to the high number of assignment conditions included; or (iv) they are limited by the assumption that only one resource is responsible for each process activity and hence, collaborative activities are disregarded. To overcome these issues, we present an integrated process mining framework that provides extensive support for the discovery of resource assignment and teamwork patterns.},
}