Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An overview of workflow management: from process modeling to workflow automation infrastructure
Distributed and Parallel Databases - Special issue on software support for work flow management
Automating process discovery through event-data analysis
Proceedings of the 17th international conference on Software engineering
Event-based detection of concurrency
SIGSOFT '98/FSE-6 Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering
Mining features for sequence classification
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Small is beautiful: discovering the minimal set of unexpected patterns
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient and tumble similar set retrieval
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Behavior-consistent specialization of object life cycles
ACM Transactions on Software Engineering and Methodology (TOSEM)
Atomicity and isolation for transactional processes
ACM Transactions on Database Systems (TODS)
Data & Knowledge Engineering - Building web warehouse
Extracting ontological concepts for tendering conceptual structures
Data & Knowledge Engineering
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Alternative Way to Analyze Workflow Graphs
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Data reduction: feature selection
Handbook of data mining and knowledge discovery
Integrating Light-Weight Workflow Management Systems within Existing Business Environments
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Defining specialization for dataflow diagrams
Information Systems
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
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
iBOM: A Platform for Intelligent Business Operation Management
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Clustering documents into a web directory for bootstrapping a supervised classification
Data & Knowledge Engineering - Special issue: WIDM 2003
Interactive workflow mining: requirements, concepts and implementation
Data & Knowledge Engineering - Special issue: Business process management
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Discovering Expressive Process Models by Clustering Log Traces
IEEE Transactions on Knowledge and Data Engineering
Efficient exact set-similarity joins
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Category ranking for personalized search
Data & Knowledge Engineering
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Efficient mining of generalized association rules with non-uniform minimum support
Data & Knowledge Engineering
An algebra for specifying valid compound terms in faceted taxonomies
Data & Knowledge Engineering
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
Conformance checking of processes based on monitoring real behavior
Information Systems
Mining most specific workflow models from event-based data
BPM'03 Proceedings of the 2003 international conference on Business process management
Behavior consistent inheritance in UML
ER'00 Proceedings of the 19th international conference on Conceptual modeling
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
Mining hierarchies of models: from abstract views to concrete specifications
BPM'05 Proceedings of the 3rd international conference on Business Process Management
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
Constraint acquisition for Entity-Relationship models
Data & Knowledge Engineering
Abstractions in Process Mining: A Taxonomy of Patterns
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Mining association rules to support resource allocation in business process management
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Bridging abstraction layers in process mining by automated matching of events and activities
BPM'13 Proceedings of the 11th international conference on Business Process Management
Slice, mine and dice: complexity-aware automated discovery of business process models
BPM'13 Proceedings of the 11th international conference on Business Process Management
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Process mining techniques have been receiving great attention in the literature for their ability to automatically support process (re)design. Typically, these techniques discover a concrete workflow schema modelling all possible execution patterns registered in a given log, which can be exploited subsequently to support further-coming enactments. In this paper, an approach to process mining is introduced that extends classical discovery mechanisms by means of an abstraction method aimed at producing a taxonomy of workflow models. The taxonomy is built to capture the process behavior at different levels of detail. Indeed, the most-detailed mined models, i.e., the leafs of the taxonomy, are meant to support the design of concrete workflows, as it happens with existing techniques in the literature. The other models, i.e., non-leaf nodes of the taxonomy, represent instead abstract views over the process behavior that can be used to support advanced monitoring and analysis tasks. All the techniques discussed in the paper have been implemented, tested, and made available as a plugin for a popular process mining framework (ProM). A series of tests, performed on different synthesized and real datasets, evidenced the capability of the approach to characterize the behavior encoded in input logs in a precise and complete way, achieving compelling conformance results even in the presence of complex behavior and noisy data. Moreover, encouraging results have been obtained in a real-life application scenario, where it is shown how the taxonomical view of the process can effectively support an explorative ex-post analysis, hinged on the different kinds of process execution discovered from the logs.