Automating process discovery through event-data analysis
Proceedings of the 17th international conference on Software engineering
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
Discovering Workflow Performance Models from Timed 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
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Mining and Reasoning on Workflows
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Case handling: a new paradigm for business process support
Data & Knowledge Engineering
Interactive workflow mining: requirements, concepts and implementation
Data & Knowledge Engineering - Special issue: Business process management
A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs
Data Mining and Knowledge Discovery
Discovering Expressive Process Models by Clustering Log Traces
IEEE Transactions on Knowledge and Data Engineering
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
Mining process models with non-free-choice constructs
Data Mining and Knowledge Discovery
Quantifying process equivalence based on observed behavior
Data & Knowledge Engineering
Improved model management with aggregated business process models
Data & Knowledge Engineering
On managing business processes variants
Data & Knowledge Engineering
Workflow simulation for operational decision support
Data & Knowledge Engineering
Towards workflow-driven database system workload modeling
Proceedings of the Second International Workshop on Testing Database Systems
ViDE: A Vision-Based Approach for Deep Web Data Extraction
IEEE Transactions on Knowledge and Data Engineering
ProM 4.0: comprehensive support for real process analysis
ICATPN'07 Proceedings of the 28th international conference on Applications and theory of Petri nets and other models of concurrency
Mining invisible tasks from event logs
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
BPM'06 Proceedings of the 4th international conference on Business Process Management
Detecting implicit dependencies between tasks from event logs
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
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
Process mining for ubiquitous mobile systems: an overview and a concrete algorithm
UMICS'04 Proceedings of the Second CAiSE conference on Ubiquitous Mobile Information and Collaboration Systems
Conformance testing: measuring the fit and appropriateness of event logs and process models
BPM'05 Proceedings of the Third international conference on Business Process Management
Towards implicit knowledge discovery from ontology change log data
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
An empirical evaluation of process mining algorithms based on structural and behavioral similarities
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Discovering process models from event multiset
Expert Systems with Applications: An International Journal
Simplifying discovered process models in a controlled manner
Information Systems
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Process mining is helpful for deploying new business processes as well as auditing, analyzing and improving the already enacted ones. Most of the existing process mining algorithms have some problems in dealing with invisible tasks, i.e., such tasks that exist in a process model but not in its event log. In this paper, a new process mining algorithm named @a^# is proposed, which extends the mining capability of the classical @a algorithm by supporting the detection of prime invisible tasks from event logs. Prime invisible tasks are divided into five types according to their structural features, i.e., INITIALIZE, SKIP, REDO, SWITCH and FINALIZE. After that, a new ordering relation for detecting mendacious dependencies between tasks that reflects prime invisible tasks is introduced. A reduction rule for identifying redundant ''mendacious'' dependencies is also considered. The construction algorithm to insert prime invisible tasks of SKIP/REDO/SWITCH types is presented. The @a^# algorithm has been evaluated using both artificial and real-life logs and the results are promising.