Abstract
In Artificial Intelligence, and, specifically in Machine Learning, to form a new notion usually means to build up a “concept” or a “category”. The simplest way to consider a category is extensional: a category is a set of “equivalent” objects,1 i.e., objects that share properties.2 Categories are organized into taxonomies, linked through the set inclusion relation.1 A concept is sometime considered as the intensional representation of a category, i.e., a description of the objects in the category,2 called also the instances of the concept. Actually, most frequently, the denotations “concept” and “category” are used as synonyms.
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Saitta, L., Esposito, R. (2001). Notion Formation in Machine Learning. In: Cantoni, V., Di Gesù, V., Setti, A., Tegolo, D. (eds) Human and Machine Perception 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1361-2_20
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DOI: https://doi.org/10.1007/978-1-4615-1361-2_20
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