Machine Learning
Ontology is called a "dictionary of concepts". It is made up of hierarchies and networks of concepts in various words.
For example, subordinate concepts of "car" include "truck", "sedan", "van", etc., and a hierarchical structure can be created.
Ontologies seem to be attracting attention in the semantic analysis of the net (semantic web), but they are trying to handle meanings and concepts of things with computers, and they are one of the foundations of various fields. Comprehensively and systematically summarizing things by analyzing the hierarchical structure of words is the central content of thinking methods and Value Engineering. However, if you try it, you will find that the nuances of words depend on the ability of the analyst and the amount of adjustment. It can also be evaluated. In academic fields such as value engineering that deal with quality at the time of design, there are times when the function of a product is divided into elements and discussed. It doesn't seem to have a name, but something close to a "functional ontology" has been created.
If you want reproducibility, objectivity, and completeness in an ontology, you also need the perspectives of mathematics, logic, and cognitive science. The symbols of logic appear, and the threshold is high, and I don't understand it well, but it seems to be indispensable for constructing an ontology.
NEXT Machine Learning