L J Mazlack
ABSTRACT
This is a theoretical expositional exploration into the underlying needs of concept formation. The main purpose is to identify and discuss the differing forms of categorization in the context of possible machine learning and representation of those concepts. Conceptualization is the process of developing the abstractions that are needed to support reasoning. The formation of the machine equivalent of human concepts is critical to the development of a general, machine based reasoning capacity. An aid in understanding conceptual categorization is prototype theory. It helps to identify the building block tools that are used to construct categories and taxonomies. When developing taxonomic structures, framing conflicts can occur in terms of how things should be clustered together, what should be the relative hierarchal levels, and what should be subordinate to what.
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Index Terms
- Taxonomic ambiguities in category variations needed to support machine conceptualization
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