DFKI Research Report-92-38



Language: English

by Philipp Hanschke, Manfred Meyer

An Alternative to Theta-Subsumption Based on Terminological Reasoning

9 Pages


Clause subsumption and rule ordering are long-standing research topics in machine learning (ML). Since logical implication can be reduced to rule-subsumption, the general subsumption problem for Horn clauses is undecidable [Plotkin, 1971b]. In this paper we suggest an alternative knowledge-representation formalism for ML that is based on a terminological logic. It provides a decidable rule-ordering which is at least as powerful as Theta-subsumption.

This document is available as PDF-File(8,9MB).

The next abstract is here, and the previous abstract is here.

DFKI-Bibliothek (bib@dfki.uni-kl.de)

Note: This page was written to look best with CSS stylesheet support Level 1 or higher. Since you can see this, your browser obviously doesn't support CSS, or you have turned it off. We highly recommend you use a browser that supports and uses CSS, and review this page once you do. However, don't fear, we've tried to write this page to still work and be readable without CSS.