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CoMinDS 2022 : Workshop on Collaborative Mining for Distributed Systems | |||||||||||||
Link: https://www.discotec.org/2022/cominds | |||||||||||||
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Call For Papers | |||||||||||||
Nowadays, organizations increasingly need to coordinate to achieve their goals collaboratively and create new forms of business. This requires organizations to form (business-oriented) distributed systems, guaranteeing their interoperability. However, this task is made complex by the need to coordinate the interactions of various participants, dealing with requirements, constraints, and regulations coming from different organizations. In addition, many business scenarios started to involve more automated and highly distributed components such as robots and smart devices that perceive and interact with the dynamics arising from the physical world. Effective coordination and cooperation of such distributed systems demand the compatibility of the processes performed by each system component. Such cooperation can be supported by the observations of the whole systems’ behavior through collaborative mining, i.e., process mining applied in the presence of heterogeneous data produced by the system components, i.e., distributed event logs. Collaborative mining techniques address the discovery of collaborative models, thus fostering the coordination aspects that typically occur on distributed systems. The objective of the CoMinDS workshop is to attract researchers and industry practitioners to discuss collaborative mining and present open challenges, state of the art, in-progress research, and practical experiences, including case studies.
The topics of the workshop include, but are not limited to: - Construction of Distributed Event Logs - Discovery of Collaborative Models - Conformance Analysis for Collaborative Models - Multi-perspective Collaborative Mining - Privacy-preserving Collaborative Process Mining - Distributed Systems Monitoring and Repair - Collaborative Decision Mining - Streaming Collaborative Mining CoMinDs is an activity of the IEEE Task Force on Process Mining |
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