Simplified Process Model Discovery Based on Role-Oriented Genetic Mining
Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/298592 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832563059998064640 |
|---|---|
| author | Weidong Zhao Xi Liu Weihui Dai |
| author_facet | Weidong Zhao Xi Liu Weihui Dai |
| author_sort | Weidong Zhao |
| collection | DOAJ |
| description | Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies. |
| format | Article |
| id | doaj-art-7d49546947284057898f528ae725297d |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-7d49546947284057898f528ae725297d2025-02-03T01:21:06ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/298592298592Simplified Process Model Discovery Based on Role-Oriented Genetic MiningWeidong Zhao0Xi Liu1Weihui Dai2Software School, Fudan University, No. 220 Handan Road, Shanghai 200433, ChinaSoftware School, Fudan University, No. 220 Handan Road, Shanghai 200433, ChinaSchool of Management, Fudan University, No. 220 Handan Road, Shanghai 200433, ChinaProcess mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.http://dx.doi.org/10.1155/2014/298592 |
| spellingShingle | Weidong Zhao Xi Liu Weihui Dai Simplified Process Model Discovery Based on Role-Oriented Genetic Mining The Scientific World Journal |
| title | Simplified Process Model Discovery Based on Role-Oriented Genetic Mining |
| title_full | Simplified Process Model Discovery Based on Role-Oriented Genetic Mining |
| title_fullStr | Simplified Process Model Discovery Based on Role-Oriented Genetic Mining |
| title_full_unstemmed | Simplified Process Model Discovery Based on Role-Oriented Genetic Mining |
| title_short | Simplified Process Model Discovery Based on Role-Oriented Genetic Mining |
| title_sort | simplified process model discovery based on role oriented genetic mining |
| url | http://dx.doi.org/10.1155/2014/298592 |
| work_keys_str_mv | AT weidongzhao simplifiedprocessmodeldiscoverybasedonroleorientedgeneticmining AT xiliu simplifiedprocessmodeldiscoverybasedonroleorientedgeneticmining AT weihuidai simplifiedprocessmodeldiscoverybasedonroleorientedgeneticmining |