Authors: Arturo Castellanos, Jeffrey Parsons, Monica Chiarini Tremblay, Roman Lukyanenko, Veda C. Storey
Tags: 2019, applications, BPMN, complex models, conceptual modeling, conceptual models, data mining, machine learning
Abstract
With the transformation of our society into a “digital world,” machine learning has emerged as an essential approach to extracting useful information from large collections of data. However, challenges remain for using machine learning effectively, some of which, we propose, can be overcome using conceptual modeling. To illustrate the potential of conceptual modeling to support machine learning, we apply machine learning to a real project supported by conceptual modeling. This exposition demonstrates the broad potential of conceptual modeling to advance machine learning by: (1) supporting the application of machine learning within organizations, (2) improving the usability of machine learning as decision tools; and (3) improving the performance of machine learning algorithms. Implications are provided for the theory and practice of conceptual modeling and machine learning.
Cite as:
Lukyanenko R., Castellanos A., Parsons J., Storey V., Tremblay M. (2019). “How Conceptual Modeling Can Support Machine Learning: Evidence from Foster Care,” in AIS SIGSAND, New York, NY, United States, June 1-2, 2019.
