Given an event log L, a control-flow discovery algorithm f, and a quality metric m, this paper faces the following problem: what are
the parameters in f that mostly influence its application in terms of
m when applied to L? This paper proposes a method to solve this problem, based on sensitivity analysis, a theory which has been successfully applied in other areas. Clearly, a satisfactory solution to this problem will be crucial to bridge the gap between process discovery algorithms and final users. Additionally, recommendation techniques and meta-techniques like determining the representational bias of an algorithm may benefit from solutions to the problem considered in this paper. The method has been evaluated over a set of logs and the flexible heuristic miner, and the preliminary results witness the applicability of the general framework described
in this paper.
CitationRibeiro, J., Carmona, J. A method for assessing parameter impact on control-flow discovery algorithms. A: International Workshop on Algorithms & Theories for the Analysis of Event Data. "Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data: Brussels, Belgium, June 22-23, 2015". Bruselas: CEUR-WS.org, 2015, p. 83-96.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: email@example.com