A
Artem Polyvyanyy
Researcher at University of Melbourne
Publications - 136
Citations - 2802
Artem Polyvyanyy is an academic researcher from University of Melbourne. The author has contributed to research in topics: Process modeling & Process mining. The author has an hindex of 28, co-authored 118 publications receiving 2234 citations. Previous affiliations of Artem Polyvyanyy include Queensland University of Technology & University of Potsdam.
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Statistical Tests and Association Measures for Business Processes
TL;DR: In this article , the authors present several statistical tests and association measures that treat process behaviour as a variable and evaluate the sensitivity of these tests to their parameters, and their applicability is illustrated through the use of real-life event logs.
Posted Content
All That Glitters Is Not Gold: Towards Process Discovery Techniques with Guarantees
Jan Martijn E. M. van der Werf,Artem Polyvyanyy,Bart R. van Wensveen,Matthieu J. S. Brinkhuis,Hajo A. Reijers +4 more
TL;DR: In this paper, a call to the community of IS engineers to complement their process discovery algorithms with properties that relate qualities of their inputs to those of their outputs is made, along with concrete guidelines for the formulation of relevant properties and experimental validation.
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Process Model Forecasting Using Time Series Analysis of Event Sequence Data
TL;DR: In this paper, the authors develop a technique to forecast the entire process model from historical event data, where a forecasted model is a will-be process model representing a probable future state of the overall process.
Journal ArticleDOI
Process model forecasting and change exploration using time series analysis of event sequence data
TL;DR: In this article , the authors develop a technique to forecast the entire process model from historical event data, which is a will-be process model representing a probable description of the overall process for a given period in the future.
Posted Content
Automated Repair of Process Models with Non-Local Constraints Using State-Based Region Theory
TL;DR: This paper proposes a novel approach for enhancing free-choice process models by adding non-free-choice constructs discovered a-posteriori via region-based techniques and proves that it preserves fitness with respect to the event log while improving the precision when indirect dependencies exist.