Method for the semantic indexing of concept hierarchies, uniform representation, use of relational database systems and generic and case-based reasoning
Uwe Petersohn, Sandra Zimmer, Jens Lehmann
TL;DR
The paper introduces a method for semantic indexing of concept hierarchies and a uniform representation that integrates with relational databases. It formalizes an indexing algorithm that assigns keys $X=[a_1,...,a_m]$ to concepts, enabling partial unification with more specific concepts and ensuring semantic correctness. It also extends to multiaxial descriptions and deduced concepts (d-concepts), and shows how logic-, concept-, and case-based reasoning can operate over the uniform representation. The approach is demonstrated in a medical knowledge base (iSuite) and emphasizes efficient storage, retrieval, and inference in relational databases.
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.