Automated merging of conflicting knowledge bases, using a consistent, majority-rule approach with knowledge-form maintenance

This paper discusses an automated process of merging conflicting information from disparate sources into a combined knowledge base. The algorithm provided generates a mathematically consistent, majority-rule merging by assigning weights to the various sources. The sources may be either conflicting portions of a single knowledge base or multiple knowledge bases. Particular attention is paid to maintaining the original rule format of the knowledge, while ensuring logical equivalence. This preservation of rule format keeps the knowledge in a more intuitive implication form as opposed to a collection of clauses with many possible logical roots. It also facilitates tracking using the support for each deductive result so that final knowledge in rule form can be ascribed back to original experts. As the approach is fairly involved mathematically, an automated procedure is developed.