A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Discovering Expressive Process Models by Clustering Log Traces
IEEE Transactions on Knowledge and Data Engineering
DECLARE: Full Support for Loosely-Structured Processes
EDOC '07 Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference
Verifiable agent interaction in abductive logic programming: The SCIFF framework
ACM Transactions on Computational Logic (TOCL)
Process Mining: Overview and Outlook of Petri Net Discovery Algorithms
Transactions on Petri Nets and Other Models of Concurrency II
Construction of Process Models from Example Runs
Transactions on Petri Nets and Other Models of Concurrency II
Online Interaction Analysis Framework for Ad-Hoc Collaborative Processes in SOA-Based Environments
Transactions on Petri Nets and Other Models of Concurrency II
Inducing declarative logic-based models from labeled traces
BPM'07 Proceedings of the 5th international conference on Business process management
Applying inductive logic programming to process mining
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
A declarative approach for flexible business processes management
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
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
25 years of applications of logic programming in Italy
A 25-year perspective on logic programming
Probabilistic declarative process mining
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Improved artificial negative event generation to enhance process event logs
CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
A knowledge-based integrated approach for discovering and repairing declare maps
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
Discovering data-aware declarative process models from event logs
BPM'13 Proceedings of the 11th international conference on Business Process Management
A Logic Framework for Incremental Learning of Process Models
Fundamenta Informaticae
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In the last few years, there has been a growing interest in the adoption of declarative paradigms for modeling and verifying process models. These paradigms provide an abstract and human understandable way of specifying constraints that must hold among activities executions rather than focusing on a specific procedural solution. Mining such declarative descriptions is still an open challenge. In this paper, we present a logic-based approach for tackling this problem. It relies on Inductive Logic Programming techniques and, in particular, on a modified version of the Inductive Constraint Logic algorithm. We investigate how, by properly tuning the learning algorithm, the approach can be adopted to mine models expressed in the ConDec notation, a graphical language for the declarative specification of business processes. Then, we sketch how such a mining framework has been concretely implemented as a ProM plug-in called DecMiner. We finally discuss the effectiveness of the approach by means of an example which shows the ability of the language to model concurrent activities and of DecMiner to learn such a model.