The International Conference on Process Mining (ICPM) aims to become 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, evidence-based focus on understanding, analyzing, and improving business processes. Compared with other data-driven research areas such as machine learning or data mining, process mining differs in the fundamental assumptions that data is generated in the context of more or less structured processes, and that the data contains explicit references to instances of these processes. Another key difference with other data-analysis techniques is that analysis results have to be explained in the context of these (interacting) processes.
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 2020 will be organized by the University of Padua, the fifth oldest university in the world, being founded in 1222.
TOPICS FOR RESEARCH PAPERS
ICPM 2020 encourages papers on new techniques and applications for process mining, as well as case studies coming from industrial scenarios. Also, papers describing novel process mining tools are expected. For new techniques, the availability of an implementation (which has to be accessible by the reviewers) is essential. Authors are expected to provide insights into the performance of new techniques on established, publicly-available benchmark datasets, or to release their datasets for replicability purposes. Empirical papers should build, where possible, on novel datasets previously unpublished, while research on existing datasets must clearly explain the novelty of the applied analysis.
Selected, accepted research papers will be considered for publication in extended and revised form in a special issue of an international journal.
The thematic areas in which contributions are sought to include, but are not limited to, those listed below.
Process mining techniques:
- Automated Discovery of Process models
- Conformance/compliance analysis
- Construction of Event Logs
- Improving quality of Event Logs
- Decision Mining for Processes
- Mining from non-process-aware systems / event streams
- Multi-perspective Process Mining
- Simulation/optimization and Process Mining
- Predictive Process Analytics
- Prescriptive Process Analytics and Recommender Systems
- Responsible Process Mining
- Privacy-preserving Process Mining
- Comparative Process Mining
- Process Model Repair
- Process Performance Mining
- Process mining Quality Measures
- Variants/deviance Analysis and Root-cause Analysis
- Visual Process Analytics
Applications and case studies in:
- Blockchain Technologies
- Business Activity Monitoring and Business Intelligence
- Business Process Management
- (Cyber) Security and Privacy
- Operations Management and Lean Six Sigma
- Process Performance Measurement
- Process Reengineering
- Resource Management
- Risk Management
- Robotic Process Automation (RPA)
- Sensors, Internet-of-Things (IoT) and wearable devices
- Specific domains such as accounting, finance, government, healthcare, manufacturing
Submissions must be original contributions that have not been published previously, nor submitted elsewhere while being submitted to ICPM 2020. All files must be prepared using the latest IEEE Computational Intelligence Society conference proceedings guidelines (8.5″ × 11″ two-column format).
The page limit is set to 8 pages (IEEE Format). All papers must be in English. Templates are available for Latex and Word here.
The paper should be submitted through the ICPM 2020 submission system, which is reachable at https://easychair.org/conferences/?conf=icpm2020 where one should select “Research Track”.
At least one author of each accepted contribution is expected to register for the conference and present the paper, along with signing a copyright release form.
- Abstract Submissions: 24 June, 2020 15 July, 2020
- Full-Paper Submissions: 1 July, 2020 15 July, 2020
- Notification: 5 August 2020 9 August 2020
- Camera-ready Submissions: 2 September 2020