mlsanityData to 7 Oct 2026

Pairing Conceptual Modeling with Machine Learning

arXiv 2106.14251 ↗First posted 27 Jun 2021cs.SE cs.AI cs.LGcited by 3

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Abstract (arXiv)

Both conceptual modeling and machine learning have long been recognized as important areas of research. With the increasing emphasis on digitizing and processing large amounts of data for business and other applications, it would be helpful to consider how these areas of research can complement each other. To understand how they can be paired, we provide an overview of machine learning foundations and development cycle. We then examine how conceptual modeling can be applied to machine learning and propose a framework for incorporating conceptual modeling into data science projects. The framework is illustrated by applying it to a healthcare application. For the inverse pairing, machine learning can impact conceptual modeling through text and rule mining, as well as knowledge graphs. The pairing of conceptual modeling and machine learning in this this way should help lay the foundations for future research.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 34 of its 242 references that are in the map. First posted on arXiv 27 Jun 2021.

Builds on

34 of 242 references.

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22 more
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Cited by year

Citing papers per year: 2023: 1; 2024: 1; 2025: 1.

3 papers.

  1. 2024How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directionscited by 5
  2. 2023Conceptual Modeling and Artificial Intelligence: A Systematic Mapping Studycited by 0
  3. 2025Domain Knowledge in Artificial Intelligence: Using Conceptual Modeling to Increase Machine Learning Accuracy and Explainabilitycited by 0