Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Workflow management: models, methods, and systems
Workflow management: models, methods, and systems
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Computers in Industry - Special issue: Process/workflow mining
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Automated construction of web accessibility models from transaction click-streams
Proceedings of the 18th international conference on World wide web
Improving bug triage with bug tossing graphs
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Discovering Structured Event Logs from Unstructured Audit Trails for Workflow Mining
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Learning the Control-Flow of a Business Process Using ICN-Based Process Models
ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
σ-algorithm: structured workflow process mining through amalgamating temporal workcases
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Mining program workflow from interleaved traces
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining process models with prime invisible tasks
Data & Knowledge Engineering
Content-aware resolution sequence mining for ticket routing
BPM'10 Proceedings of the 8th international conference on Business process management
Probabilistic declarative process mining
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
A quest for beauty and wealth (or, business processes for database researchers)
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
RECYCLE: Learning looping workflows from annotated traces
ACM Transactions on Intelligent Systems and Technology (TIST)
Mining models of composite web services for performance analysis
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
BPM'06 Proceedings of the 4th international conference on Business Process Management
A Study of Quality and Accuracy Trade-offs in Process Mining
INFORMS Journal on Computing
| Hi-index | 0.00 |
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model of such processes is developed, and it becomes important to know if such a model is actually being followed by analyzing the available activity logs. In other scenarios, no model is available and, with the purpose of evaluating cases or creating new production policies, one is interested in learning a workflow representation of such activities. In either case, machine learning tools that can mine workflow models are of great interest and still relatively unexplored. We present here a probabilistic workflow model and a corresponding learning algorithm that runs in polynomial time. We illustrate the algorithm on example data derived from a real world workflow.