Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Workflow management: models, methods, and systems
Workflow management: models, methods, and systems
A Machine Learning Approach to Workflow Management
ECML '00 Proceedings of the 11th European Conference on Machine Learning
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-Based Process Monitoring and Controlling ¾ Technical and Organizational Issues
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Mining process models with non-free-choice constructs
Data Mining and Knowledge Discovery
Process Mining: Overview and Outlook of Petri Net Discovery Algorithms
Transactions on Petri Nets and Other Models of Concurrency II
Using Genetic Process Mining Technology to Construct a Time-Interval Process Model
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
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
Mining process models with prime invisible tasks
Data & Knowledge Engineering
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
Reality mining via process mining
AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
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Ubiquitous Mobile Systems (UMSs) allow for automated capturing of events. Both mobility and ubiquity are supported by electronic means such as mobile phones and PDAs and technologies such as RFID, Bluetooth, WLAN, etc. These can be used to automatically record human behavior and business processes in detail. UMSs typically also allow for more flexibility. The combination of flexibility (i.e., the ability to deviate from standard procedures) and the automated capturing of events, provides an interesting application domain for process mining. The goal of process mining is to discover process models from event logs. The α-algorithm is a process mining algorithm whose application is not limited to ubiquitous and/or mobile systems. Unfortunately, the α-algorithm is unable to tackle so-called “short loops”, i.e., the repeated occurrence of the same event. Therefore, a new algorithm is proposed to deal with short loops: the α+-algorithm. This algorithm has been implemented in the EMiT tool.