activity
20182021
most citedVisual Drift Detection for Sequence Data Analysis of Business Processes

50 citations · 84 across the 8 of their papers we have counts for

collaborators

11 papers

cs.SE2021

Discovering executable routine specifications from user interaction logs

Volodymyr Leno, Adriano Augusto, Marlon Dumas +3

Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applica…

cs.LG2021

Process Model Forecasting Using Time Series Analysis of Event Sequence Data

Johannes De Smedt, Anton Yeshchenko, Artem Polyvyanyy +2

Process analytics is an umbrella of data-driven techniques which includes making predictions for individual process instances or overall process models. At the instance level, vari…

cs.SE20208 cited

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 +2

The aim of a process discovery algorithm is to construct from event data a process model that describes the underlying, real-world process well. Intuitively, the better the quality…

cs.HC202050 cited

Visual Drift Detection for Sequence Data Analysis of Business Processes

Anton Yeshchenko, Claudio Di Ciccio, Jan Mendling +1

Event sequence data is increasingly available in various application domains, such as business process management, software engineering, or medical pathways. Processes in these dom…

cs.AI20206 cited

Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining

Artem Polyvyanyy, Hanan Alkhammash, Claudio Di Ciccio +6

This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from informa…

cs.LG2020

Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs

Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas +2

This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given…