Multi-Connected Ontologies

TL;DR

This paper critiques current ontology structures and proposes a novel multi-connected complex network model represented as an asymmetric probability matrix to better capture diverse expressions of knowledge domains.

Contribution

It introduces a new multi-connected complex network framework for ontologies, extending beyond traditional structures to enhance representational capacity.

Findings

Traditional ontologies are insufficient for representing diverse knowledge expressions.

The proposed multi-connected structure is modeled as an asymmetric probability matrix.

This new approach offers a richer, more flexible representation of subject domains.

Abstract

Ontologies have been used for the purpose of bringing system and consistency to subject and knowledge areas. We present a criticism of the present mathematical structure of ontologies and indicate that they are not sufficient in their present form to represent the many different valid expressions of a subject knowledge domain. We propose an alternative structure for ontologies based on a richer multi connected complex network which contains the present ontology structure as a projection. We demonstrate how this new multi connected ontology should be represented as an asymmetric probability matrix.