Method for the semantic indexing of concept hierarchies, uniform representation, use of relational database systems and generic and case-based reasoning

TL;DR

This paper introduces a semantic indexing method for concept hierarchies that enables uniform representation and reasoning using relational databases, enhancing knowledge management and inference capabilities.

Contribution

It proposes a novel indexing algorithm for concept hierarchies that ensures semantic correctness and unifiability, integrating relational databases with case-based reasoning.

Findings

Proven correctness and completeness of the indexing algorithm

Effective storage of instances in relational databases

Enabling inference through case-based reasoning

Abstract

This paper presents a method for semantic indexing and describes its application in the field of knowledge representation. Starting point of the semantic indexing is the knowledge represented by concept hierarchies. The goal is to assign keys to nodes (concepts) that are hierarchically ordered and syntactically and semantically correct. With the indexing algorithm, keys are computed such that concepts are partially unifiable with all more specific concepts and only semantically correct concepts are allowed to be added. The keys represent terminological relationships. Correctness and completeness of the underlying indexing algorithm are proven. The use of classical relational databases for the storage of instances is described. Because of the uniform representation, inference can be done using case-based reasoning and generic problem solving methods.