http://dl.gi.de/handle/20.500.12116/30637 2026-07-25T04:16:53Z 2026-07-25T04:16:53Z Janssenswillen, Gert Depaire, Benoît http://dl.gi.de/handle/20.500.12116/30646 2019-12-13T06:33:01Z 2019-01-01T00:00:00Z

Towards Confirmatory Process Discovery: Making Assertions About the Underlying System Janssenswillen, Gert; Depaire, Benoît The focus in the field of process mining, and process discovery in particular, has thus far been on exploring and describing event data by the means of models. Since the obtained models are often directly based on a sample of event data, the question whether they also apply to the real process typically remains unanswered. As the underlying process is unknown in real life, there is a need for unbiased estimators to assess the system-quality of a discovered model, and subsequently make assertions about the process. In this paper, an experiment is described and discussed to analyze whether existing fitness, precision and generalization metrics can be used as unbiased estimators of system fitness and system precision. The results show that important biases exist, which makes it currently nearly impossible to objectively measure the ability of a model to represent the system.

2019-01-01T00:00:00Z Kranz, Johann Nagel, Esther Yoo, Youngjin http://dl.gi.de/handle/20.500.12116/30648 2019-12-13T06:33:01Z 2019-01-01T00:00:00Z

Blockchain Token Sale Kranz, Johann; Nagel, Esther; Yoo, Youngjin

2019-01-01T00:00:00Z Jouck, Toon Depaire, Benoît http://dl.gi.de/handle/20.500.12116/30647 2019-12-13T06:33:01Z 2019-01-01T00:00:00Z

Generating Artificial Data for Empirical Analysis of Control-flow Discovery Algorithms Jouck, Toon; Depaire, Benoît Within the process mining domain, research on comparing control-flow (CF) discovery techniques has gained importance. A crucial building block of empirical analysis of CF discovery techniques is obtaining the appropriate evaluation data. Currently, there is no answer to the question of how to collect such evaluation data. The paper introduces a methodology for generating artificial event data (GED) and an implementation called the Process Tree and Log Generator. The GED methodology and its implementation provide users with full control over the characteristics of the generated event data and an integration within the ProM framework. Unlike existing approaches, there is no tradeoff between including long-term dependencies and soundness of the process. The contributions of the paper provide a solution for a necessary step in the empirical analysis of CF discovery algorithms.

2019-01-01T00:00:00Z Simonofski, Anthony Asensio, Estefanía Serral Smedt, Johannes Snoeck, Monique http://dl.gi.de/handle/20.500.12116/30643 2019-12-13T06:33:01Z 2019-01-01T00:00:00Z

Hearing the Voice of Citizens in Smart City Design: The CitiVoice Framework Simonofski, Anthony; Asensio, Estefanía Serral; Smedt, Johannes; Snoeck, Monique In the last few years, smart cities have attracted considerable attention because they are considered a response to the complex challenges that modern cities face. However, smart cities often do not optimally reach their objectives if the citizens, the end-users, are not involved in their design. The aim of this paper is to provide a framework to structure and evaluate citizen participation in smart cities. By means of a literature review from different research areas, the relevant enablers of citizen participation are summarized and bundled in the proposed CitiVoice framework. Then, following the design science methodology, the content and the utility of CitiVoice are validated through the application to different smart cities and through in-depth interviews with key Belgian smart city stakeholders. CitiVoice is used as an evaluation tool for several Belgian smart cities allowing drawbacks and flaws in citizens' participation to be discovered and analyzed. It is also demonstrated how CitiVoice can act as a governance tool for the ongoing smart city design of Namur (Belgium) to help define the citizen participation strategy. Finally, it is used as a comparison and creativity tool to compare several cities and design new means of participation.

2019-01-01T00:00:00Z