Synthesizing Petri nets from state-based models
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
The synthesis problem for elementary net systems is NP-complete
Theoretical Computer Science
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IEEE Transactions on Computers
Polynomial Algorithms for the Synthesis of Bounded Nets
TAPSOFT '95 Proceedings of the 6th International Joint Conference CAAP/FASE on Theory and Practice of Software Development
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CONCUR '98 Proceedings of the 9th International Conference on Concurrency Theory
Lectures on Petri Nets I: Basic Models, Advances in Petri Nets, the volumes are based on the Advanced Course on Petri Nets
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
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Data & Knowledge Engineering
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Workflow Mining: Discovering Process Models from Event Logs
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
How to synthesize nets from languages: a survey
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Process Discovery Using Integer Linear Programming
PETRI NETS '08 Proceedings of the 29th international conference on Applications and Theory of Petri Nets
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OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
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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
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OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
Fuzzy mining: adaptive process simplification based on multi-perspective metrics
BPM'07 Proceedings of the 5th international conference on Business process management
Process mining based on regions of languages
BPM'07 Proceedings of the 5th international conference on Business process management
Process mining and petri net synthesis
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
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UMICS'04 Proceedings of the Second CAiSE conference on Ubiquitous Mobile Information and Collaboration Systems
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Transactions on Petri Nets and Other Models of Concurrency II
Rbminer: a tool for discovering Petri nets from transition systems
ATVA'10 Proceedings of the 8th international conference on Automated technology for verification and analysis
Simplifying mined process models: an approach based on unfoldings
BPM'11 Proceedings of the 9th international conference on Business process management
A Study of Quality and Accuracy Trade-offs in Process Mining
INFORMS Journal on Computing
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
Simplifying discovered process models in a controlled manner
Information Systems
Discovering block-structured process models from event logs - a constructive approach
PETRI NETS'13 Proceedings of the 34th international conference on Application and Theory of Petri Nets and Concurrency
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Within the research domain of process mining, process discovery aims at constructing a process model as an abstract representation of an event log. The goal is to build a model (e.g., a Petri net) that provides insight into the behavior captured in the log. The theory of regions can be used to transform a state-based model or a set of words into a Petri net that exactly mimics the behavior given as input. Recently several papers appeared on the application of the theory of regions for process discovery. This paper provides an overview of different Petri net based discovery algorithms from both the area of process mining and the theory of regions. The overview encompasses five categories of algorithms, for which common assumptions and problems are indicated. Furthermore, based on the shortcomings of the algorithms in each category, a set of directions for future research in the process discovery area is discussed.