Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Global partial orders from sequential data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Information Retrieval
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Process Miner - A Tool for Mining Process Schemes from Event-Based Data
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Automating the Discovery of As-Is Business Process Models: Probabilistic and Algorithmic Approaches
Information Systems Research
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
Evaluating the Process Control-Flow Complexity Measure
ICWS '05 Proceedings of the IEEE International Conference on Web Services
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
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
Business process mining: An industrial application
Information Systems
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
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
IEEE Transactions on Software Engineering
Conformance checking of processes based on monitoring real behavior
Information Systems
Quantifying process equivalence based on observed behavior
Data & Knowledge Engineering
Business Process Management: Concepts, Languages, Architectures
Business Process Management: Concepts, Languages, Architectures
Mining taxonomies of process models
Data & Knowledge Engineering
Towards comprehensive support for organizational mining
Decision Support Systems
Complexity metrics for Workflow nets
Information and Software Technology
A novel approach for process mining based on event types
Journal of Intelligent Information Systems
Using minimum description length for process mining
Proceedings of the 2009 ACM symposium on Applied Computing
Robust Process Discovery with Artificial Negative Events
The Journal of Machine Learning Research
Discovering Process Models from Unlabelled Event Logs
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Discovering Process Models from Unlabelled Event Logs
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Abstractions in Process Mining: A Taxonomy of Patterns
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Discovering expressive process models from noised log data
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Top-down induction of first-order logical decision trees
Artificial Intelligence
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
New Region-Based Algorithms for Deriving Bounded Petri Nets
IEEE Transactions on Computers
What makes process models understandable?
BPM'07 Proceedings of the 5th international conference on Business process management
Fuzzy mining: adaptive process simplification based on multi-perspective metrics
BPM'07 Proceedings of the 5th international conference on Business process management
Inducing declarative logic-based models from labeled traces
BPM'07 Proceedings of the 5th 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
A fresh look at precision in process conformance
BPM'10 Proceedings of the 8th international conference on Business process management
Time prediction based on process mining
Information Systems
Discovering process models with genetic algorithms using sampling
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Process discovery in event logs: An application in the telecom industry
Applied Soft Computing
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process diagnostics using trace alignment: Opportunities, issues, and challenges
Information Systems
Towards mining structural workflow patterns
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
Hierarchical conformance checking of process models based on event logs
PETRI NETS'13 Proceedings of the 34th international conference on Application and Theory of Petri Nets and Concurrency
Slice, mine and dice: complexity-aware automated discovery of business process models
BPM'13 Proceedings of the 11th international conference on Business Process Management
Business process mining from e-commerce web logs
BPM'13 Proceedings of the 11th international conference on Business Process Management
Conformance checking in the large: partitioning and topology
BPM'13 Proceedings of the 11th international conference on Business Process Management
Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port
Expert Systems with Applications: An International Journal
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Process mining is the research domain that is dedicated to the a posteriori analysis of business process executions. The techniques developed within this research area are specifically designed to provide profound insight by exploiting the untapped reservoir of knowledge that resides within event logs of information systems. Process discovery is one specific subdomain of process mining that entails the discovery of control-flow models from such event logs. Assessing the quality of discovered process models is an essential element, both for conducting process mining research as well as for the use of process mining in practice. In this paper, a multi-dimensional quality assessment is presented in order to comprehensively evaluate process discovery techniques. In contrast to previous studies, the major contribution of this paper is the use of eight real-life event logs. For instance, we show that evaluation based on real-life event logs significantly differs from the traditional approach to assess process discovery techniques using artificial event logs. In addition, we provide an extensive overview of available process discovery techniques and we describe how discovered process models can be assessed regarding both accuracy and comprehensibility. The results of our study indicate that the HeuristicsMiner algorithm is especially suited in a real-life setting. However, it is also shown that, particularly for highly complex event logs, knowledge discovery from such data sets can become a major problem for traditional process discovery techniques.