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Dec 2, 2023 · Abstract. With Artificial Intelligence and Machine Learning (ML) on the rise, organisations of different scales and.
This paper aims to address some of these challenges by proposing an ontology for ensuring the reproducibility of ML models in research as well as their ...
An Application Ontology for Reproducibility of Machine Learning Solutions. Conference. An Application Ontology for Reproducibility of Machine Learning Solutions.
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Aug 17, 2023 · This systematic literature review aimed to explore the challenges and limitations of applying ontology driven machine learning models to the ...
The feasibility of the proposed approach has been demonstrated in a real-world scenario and it is expected to pave the way towards unlocking the full potential ...
transforms it into clean, 'self-describing', machine-readable data. It uses established, controlled ontologies to apply an explicit, unique identifier ...
Jun 29, 2024 · Abstract: Machine Learning (ML) systems are capable of reproducing and often amplifying un- desired biases. This puts emphasis on the ...
Mar 3, 2021 · An ontology allows for the representation of vastly complex domain knowledge in a structural graphical form. This in turn raises challenges ...
Missing: Reproducibility | Show results with:Reproducibility
Applying machine learning to our context raises the question of which learning algorithm to use and which types of information to use in the learning.
This chapter studies ontology matching: the problem of finding the semantic mappings between two given ontologies. This problem lies at the heart of ...