title: Knowledge base version reintegration.
abstract: Given two versions of a knowledge base (KB), independently modified, we investigated the problem of incorporating changes made to one KB version into the other. We have implemented a system that will perform such a reintegration, autonomously, using predetermined user preferences. This effort has lead to a greater insight into the version reintegration problem and has highlighted those areas where user intervention would be the most beneficial in a semi-autonomous system.
authors.affiliation: Structural Informatics Group, Departments of Biological Structure and Medical Education and Biomedical Informatics, University of Washington, Seattle, WA 98195, USA.
authors.forename: Landon T
authors.initials: LT
authors.lastname: Detwiler
authors.forename: Cornelius
authors.initials: C
authors.lastname: Rosse
mesh_terms: D000715:Anatomy / Q000145:classification*; D006801:Humans; D051188:Knowledge Bases; D008953:Models, Anatomic