Guided Interaction Exploration in Artifact-centric Process Models

@article{Eck2017GuidedIE,
  title={Guided Interaction Exploration in Artifact-centric Process Models},
  author={Maikel L. van Eck and Natalia V. Sidorova and Wil M.P. van der Aalst},
  journal={2017 IEEE 19th Conference on Business Informatics (CBI)},
  year={2017},
  volume={01},
  pages={109-118}
}
Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. [] Key Method The approach has been fully implemented as a ProM plug-in; the CSM Miner provides an interactive artifact-centric process discovery tool focussing on interactions. The approach has been evaluated using real life data sets, including the personal loan and overdraft process of a Dutch financial institution.
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References

SHOWING 1-10 OF 15 REFERENCES

Artifact Lifecycle Discovery

This article presents a method for automated discovery of artifact-centric process models starting from logs consisting of flat collections of event records so that a wide range of existing (non-artifact-centric) automated process discovery methods can be reused in a flexible manner.

Discovering and Exploring State-Based Models for Multi-perspective Processes

This work aims to discover models for processes where different facets, or perspectives, of the process can be identified and presents a formalisation of these relations and an approach to discover state-based models highlighting them.

Discovering Hierarchical Process Models Using ProM

This paper demonstrates the discovery of hierarchical process models using a set of interrelated plugins implemented in ProM, enabled through the automated discovery of abstractions (of activities) with domain significance.

Discovering Unbounded Synchronization Conditions in Artifact-Centric Process Models

A method to automatically discover synchronization conditions over a variable-sized set of events such as for example that a purchasing decision is made only if at least three out of an a priori undetermined set of quotes have been received is proposed.

Composite State Machine Miner: Discovering and Exploring Multi-perspective Processes

An interactive process discovery tool that can be used to discover and explore state-based models for multi-perspective processes where different facets, or perspectives, of the process can be identified is described.

Mining Process Performance from Event Logs

It is shown that alignments between event logs and discovered process models from process discovery algorithms reveal insights into frequently occurring deviations and how such insights can be exploited to repair the original process models to better reflect reality.

Proclets: A Framework for Lightweight Interacting Workflow Processes

This paper introduces and advocates the use of interacting proclets, i.e. lightweight workflow processes, so that by promoting interactions to first-class citizens it is possible to model complex workflows in a more natural manner.

Active Trace Clustering for Improved Process Discovery

In an assessment using four complex, real-life event logs, it is shown that this technique significantly outperforms currently available trace clustering techniques.

Discovering Interacting Artifacts from ERP Systems

A new semi-automatic, end-to-end approach for analyzing event data in a plain database of an ERP system for unusual executions is presented, identifying an artifact-centric process model describing the business objects, their life-cycles, and how the various objects interact along their lives-cycles.

Process Mining-Driven Optimization of a Consumer Loan Approvals Process - The BPIC 2012 Challenge Case Study

Findings are presented on how a deep understanding of the process was developed using the event log data, potential areas of efficiency improvement within the institution’s operations and opportunities to use knowledge gathered during process execution to make predictions about likely eventual outcome of a loan application are identified.