Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Visualizing Tree Structures in Genetic Programming
Genetic Programming and Evolvable Machines
Shortcomings with using edge encodings to represent graph structures
Genetic Programming and Evolvable Machines
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
Graph structured program evolution
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Identifying structural mechanisms in standard genetic programming
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
The prom framework: a new era in process mining tool support
ICATPN'05 Proceedings of the 26th international conference on Applications and Theory of Petri Nets
Knowledge interaction with genetic programming in mechatronic systems design using bond graphs
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Crawling and Extracting Process Data from the Web
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
A GP Process Mining Approach from a Structural Perspective
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
| Hi-index | 0.00 |
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more complex there is a need for managers to understand the processes they already have in place. To undertake such a task manually would be extremely time consuming so the practice of process mining attempts to automatically reconstruct the correct representation of a process based on a set of process execution traces. This paper outlines an alternative approach to business process mining utilising a Genetic Programming (GP) technique coupled with a graph based representation. The graph based representation allows greater flexibility in the analysis of process flowchart structure and offers the possibility of mining complex business processes from incomplete or problematic event logs. A number of event logs have been mined by the GP technique featured in this paper and the results of the experimentation point towards the potential of this novel process mining approach.