A Machine Learning Approach to Workflow Management
ECML '00 Proceedings of the 11th European Conference on Machine Learning
A Data Warehouse for Workflow Logs
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Computers in Industry - Special issue: Process/workflow mining
Mining exact models of concurrent workflows
Computers in Industry - Special issue: Process/workflow mining
Computers in Industry - Special issue: Process/workflow mining
A Comprehensive and Automated Approach to Intelligent Business Processes Execution Analysis
Distributed and Parallel Databases
A case-based reasoning framework for workflow model management
Data & Knowledge Engineering - Special issue: Advances in business process management
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Improving process models by discovering decision points
Information Systems
Web process and workflow path mining using the Multimethod approach
International Journal of Business Intelligence and Data Mining
Automatic Extraction of Process Control Flow from I/O Operations
BPM '08 Proceedings of the 6th International Conference on Business Process Management
Classification and evaluation of timed running schemas for workflow based on process mining
Journal of Systems and Software
A novel approach for process mining based on event types
Journal of Intelligent Information Systems
POIROT: acquiring workflows by combining models learned from interpreted traces
Proceedings of the fifth international conference on Knowledge capture
A context driven approach for workflow mining
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Mining most specific workflow models from event-based data
BPM'03 Proceedings of the 2003 international conference on Business process management
A case-based framework for workflow model management
BPM'03 Proceedings of the 2003 international conference on Business process management
Approaching process mining with sequence clustering: experiments and findings
BPM'07 Proceedings of the 5th international conference on Business process management
RECYCLE: Learning looping workflows from annotated traces
ACM Transactions on Intelligent Systems and Technology (TIST)
Using simulation to improve the flexibility of adaptive workflow models based on temporal logic
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Incremental workflow mining based on document versioning information
SPW'05 Proceedings of the 2005 international conference on Unifying the Software Process Spectrum
Towards mining structural workflow patterns
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
A bottom-up workflow mining approach for workflow applications analysis
DEECS'06 Proceedings of the Second international conference on Data Engineering Issues in E-Commerce and Services
A Study of Quality and Accuracy Trade-offs in Process Mining
INFORMS Journal on Computing
Discovering process models from event multiset
Expert Systems with Applications: An International Journal
A Logic Framework for Incremental Learning of Process Models
Fundamenta Informaticae
| Hi-index | 0.00 |
Current workflow management systems (WFMS) offer little aid for the acquisition of workflow models and their adaptation to changing requirements. To support these activities we propose to integrate machine learning and workflow management. This enables an inductive approach to workflow acquisition and adaptation by processing traces of manually enacted workflows. We present a machine learning component that combines two different machine learning algorithms. In this paper we focus mainly on the first one, which induces the structure of the workflow, based on the induction of hidden markov models. The second algorithm, a standard decision rule induction algorithm, induces transition conditions. The main concepts have been implemented in a prototype, which we have validated using artificial process traces. The induced workflow models can be imported by the business process management system ADONIS.