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From Mental Models to Machine Learning Models via Conceptual Models

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Enterprise, Business-Process and Information Systems Modeling (BPMDS 2021, EMMSAD 2021)

Abstract

Although much research continues to be carried out on modeling of information systems, there has been a lack of work that relates the activities of modeling to human mental models. With the increased emphasis on machine learning systems, model development remains an important issue. In this research, we propose a framework for progressing from human mental models to machine learning models and implementation via the use of conceptual models. The framework is illustrated by an application to a citizen science project. Recommendations for the use of the framework are proposed.

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Notes

  1. 1.

    https://www.kaggle.com/arashnic/hr-analytics-job-change-of-data-scientists.

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Correspondence to Veda C. Storey .

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Maass, W., Storey, V.C., Lukyanenko, R. (2021). From Mental Models to Machine Learning Models via Conceptual Models. In: Augusto, A., Gill, A., Nurcan, S., Reinhartz-Berger, I., Schmidt, R., Zdravkovic, J. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2021 2021. Lecture Notes in Business Information Processing, vol 421. Springer, Cham. https://doi.org/10.1007/978-3-030-79186-5_19

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  • DOI: https://doi.org/10.1007/978-3-030-79186-5_19

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