Controlling Search for the Consequences of New Information during Knowledge Integration (1989)
K. Murray and Bruce Porter
Adding new information to an existing knowledge base can have significant consequences. For example, new information might contradict existing knowledge or reveal a "gap" in the knowledge base. Most approaches to knowledge-base refinement either ignore these consequences or compute them exhaustively. Our approach, formalized in a task called knowledge integration, is to partially elaborate the consequences of new information. A form of domain knowledge called `views' controls the search to identify non-superficial consequences of new information. A prototype knowledge integration program has been implemented and demonstrated with a complex extension to a large knowledge base.
In Proceedings of the Sixth International Workshop on Machine Learning, pp. 290-295, Ithaca, NY, June 1989.

Bruce Porter Faculty porter [at] cs utexas edu