会议信息
ICPM 2021: International Conference on Process Mining
https://icpmconference.org/2021/截稿日期: |
2021-07-01 Extended |
通知日期: |
2021-08-15 |
会议日期: |
2021-10-31 |
会议地点: |
Eindhoven, the Netherlands |
届数: |
3 |
浏览: 6590 关注: 2 参加: 1
征稿
The International Conference on Process Mining (ICPM) is the premium forum for researchers, practitioners and developers in process mining. The objective is to explore and exchange knowledge in this field through scientific talks, industry discussions, contests, technical tutorials and panels. The conference covers all aspects of process mining research and practice, including theory, algorithmic challenges, applications and connections with other fields. The conference is technically co-sponsored by the IEEE Computational Intelligence Society, and supported by the IEEE Task Force on Process Mining. Process mining is an innovative research field which focuses on extracting business process insights from transactional data commonly recorded by IT systems, with the ultimate goal of analyzing and improving organizational productivity along performance dimensions such as efficiency, quality, compliance and risk. By relying on data rather than perceptions gained from interviews and workshops, process mining shifts the way of thinking from “confidence-based” to “evidence-based” business process management. Thus, process mining distinguishes itself within the information systems domain by its fundamental focus on understanding, analyzing, and improving business processes based on process data. Current process mining challenges include scalability, i.e., dealing with volume, velocity and variability of input data, especially in real-time/online settings using event streams; approximation, i.e., balancing computation time with accuracy; understandability and explainability, i.e., providing easy-to-understand and explainable analytics; multi-perspective analysis, i.e., considering data, resources and time beyond the process control flow; measurability, e.g., providing a comprehensive framework for measuring differences between observed and modelled process behavior, and ethical and confidential aspects of process mining, i.e., how to ensure that process mining procedures and results do not violate ethical and privacy principles. ICPM 2021 will take place on October 31st-November 4th at the Campus of the Eindhoven University of Technology, The Netherlands. TOPICS FOR RESEARCH PAPERS ICPM 2021 encourages papers on new methodologies, techniques and applications for process mining, as well as case studies coming from industrial scenarios. Also, papers describing novel tools, fundamental research and empirical studies on process mining are expected. For the sake of replicability of the presented studies, the addition of supplementary resources is strongly encouraged, such as: used datasets, a publicly accessible implementation for new techniques, experimental packages for empirical studies. The use of novel, previously unpublished datasets is most welcome. Research on existing datasets must clearly showcase the novelty or unprecedented results of the applied analysis. Selected, accepted research papers will be considered for publication in an extended and revised form in a special issue of an international journal. The thematic areas in which contributions are sought include, but are not limited to, those listed below. Process mining techniques: Automated Discovery of Process Models Conformance/compliance Analysis Construction of Event Logs Event Log Quality Improvement Decision Mining for Processes Rule/constraint-based Process Mining Mining from non-process-aware systems / event streams Multi-perspective Process Mining Simulation/optimization for Process Mining Predictive Process Analytics Prescriptive Process Analytics and Recommender Systems Responsible Process Mining Privacy-preserving Process Mining Process Model Repair Process Performance Mining Variants/deviance Analysis and Root-cause Analysis Visual Process Analytics Process Monitoring Process mining fundamental research: Formal Foundations of Process Mining Comparative and Benchmark Studies on Process Mining Conceptual Models Related to Process Mining Human-centered Studies on Process Mining Process Mining Quality Measures Process Mining Guidelines Process mining applications and case studies in: Artificial Intelligence Blockchain Technologies Robotic Process Automation (RPA) Business Activity Monitoring and Business Intelligence (Cyber) Security and Privacy Operations Management and Lean Six Sigma Process Performance Measurement Process Reengineering Resource Management Risk Management Sensors, Internet-of-Things (IoT) and Wearable Devices Specific domains (such as accounting, finance, government, healthcare, manufacturing)
最后更新 Dou Sun 在 2021-06-19
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相关期刊
CCF | 全称 | 影响因子 | 出版商 | ISSN |
---|---|---|---|---|
Computational Mathematics and Modeling | Springer | 1046-283X | ||
Programming and Computer Software | 0.700 | Springer | 0361-7688 | |
Journal of Computational Analysis and Applications | Springer | 1521-1398 | ||
Quantum Information Processing | 2.200 | Springer | 1570-0755 | |
c | Real-Time Systems | 1.400 | Springer | 0922-6443 |
c | IEEE Transactions on Circuits and Systems I: Regular Papers | 5.200 | IEEE | 1549-8328 |
Mathematics of Operations Research | 1.400 | INFORMS | 0364-765X | |
Machine Learning and Applications: An International Journal | AIRCC | 2394-0840 | ||
a | IEEE Transactions on Pattern Analysis and Machine Intelligence | 20.80 | IEEE | 0162-8828 |
全称 | 影响因子 | 出版商 |
---|---|---|
Computational Mathematics and Modeling | Springer | |
Programming and Computer Software | 0.700 | Springer |
Journal of Computational Analysis and Applications | Springer | |
Quantum Information Processing | 2.200 | Springer |
Real-Time Systems | 1.400 | Springer |
IEEE Transactions on Circuits and Systems I: Regular Papers | 5.200 | IEEE |
Mathematics of Operations Research | 1.400 | INFORMS |
Machine Learning and Applications: An International Journal | AIRCC | |
IEEE Transactions on Pattern Analysis and Machine Intelligence | 20.80 | IEEE |
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