TY  - CONF
A1  - Sun, Yaguang
A1  - Bauer, Bernhard
A2  - Hammoudi, Slimane
A2  - Maciaszek, Leszek
A2  - Missikoff, Michele M.
A2  - Camp, Olivier
A2  - Cordeiro, José
T1  - A graph and trace clustering-based approach for abstracting mined business process podels
T2  - Proceedings of the 18th International Conference on Enterprise Information Systems (ICEIS 2016), April 25-28, 2016, Rome, Italy, volume 1
N2  - 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.
Y1  - 2016
UR  - https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/120042
UR  - https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-1200422
SN  - 978-989-758-187-8
SP  - 63
EP  - 74
PB  - SciTePress
CY  - Setúbal
ER  -