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Dettaglio pubblicazione

2020, Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, Pages - (volume: 2578)

Ontology-based explanation of classifiers (04b Atto di convegno in volume)

Croce F., Cima G., Lenzerini M., Catarci T.

The rise of data mining and machine learning use in many applications has brought new challenges related to classification. Here, we deal with the following challenge: how to interpret and understand the reason behind a classifier's prediction. Indeed, understanding the behaviour of a classifier is widely recognized as a very important task for wide and safe adoption of machine learning and data mining technologies, especially in high-risk domains, and in dealing with bias.We present a preliminary work on a proposal of using the Ontology-Based Data Management paradigm for explaining the behavior of a classifier in terms of the concepts and the relations that are meaningful in the domain that is relevant for the classifier.
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