INTERPRETING THE MEANING OF GEOMETRIC FEATURES BASED ON THE SIMILARITIES BETWEEN ASSOCIATIONS OF SEMANTIC NETWORK

In this paper the method of semantic network analysis which enables semantic categorization of data in the network is presented. The main goal of network analysis is determination of the similarity of associations in semantic network based on similarity of attributes values of associations. The method allows highly efficient semantic categorization of new concepts, which does not depend on pre-planned inputs and predefined rules of deduction. Also, the concept allows different semantic interpretations of the same concept in different semantic contexts. As a specific example for demonstration of semantic categorization process, a part of mold manufacturing workflow was chosen.