Using Conceptual Modeling to Support Machine Learning

Foundations of information technology based on Bunge’s systemist philosophy of reality

“…Explainable artificial intelligence (XAI) is a socio-technical challenge due to the growing need to allow a machine to precisely explain a taken decision [40,58]. It is, therefore, crucial to obtain a shared understanding of the domain under consideration (Lukyanenko et al [68,69], what again requires a conceptualization process that is hard to achieve using only the concrete (material) fundamental background that the original BWW provides. On the contrary, BSO provides constructs to support the characterization of a conventional XAI-based process [99].…”

Pairing conceptual modeling with machine learning

“…In this way, a conceptual model can serve as a social artifact with respect to the need to capture a shared conceptualization of a group [13]. Much research that attempts to understand and characterize research on the development and application of conceptual modeling (e.g., [14][15][16][17][18][19]). Accepted for publication: Data & Knowledge Engineering…”

“…Alignment of ML-based information system development with business goals and strategies is at an early stage of research and understanding [18,127]. Therefore, guidelines and frameworks are needed to identify the research topics that need to be studied and to support the progression of the needed research.…”

“…Goal modeling may become a key contribution of conceptual modeling to ML-based system development [145]. Nalchigar et al (2021), for example, propose three views for modeling goals for ML-based system development: business view, analytics design view, data preparation view [146].…”

“…Conceptual modeling is well positioned when it comes to structuring requirements for complex systems, including ML-based systems. Recent proposals structure data science development by views and goal models [145,146]. In the direction of machine learning for conceptual modeling, research issues are in their infancies.…”