R.W. Taylor
IEEE Conference on Artificial Intelligence Applications 1990
Techniques for managing problems associated with the scalability of large knowledge-based systems are presented. The discussion is based on experience in building a large knowledge-based system and on perceptions regarding future technological requirements to support ongoing development. Achieving persistence for knowledge bases (KBs) is investigated. Persistence refers to storing a knowledge base on a stable storage medium such as a magnetic disk. A knowledge base management system (KBMS) in which a large KB is concurrently developed by a team of collaborating knowledge engineers is proposed. At the heart of the KBMS is a version store, which is a persistent storage structure for a KB. To support the concurrent collaborative work, the version store maintains multiple versions of a KB such that a knowledge engineer can access and modify any version. Retrieve and update operations have been defined on the version store to efficiently access and modify any version. Objects in a version store are clustered to support efficient access of an entire version of the KB or subparts of it. The retrieval algorithm has been validated through simulation. A prototype of the version store has been implemented and is being integrated into the user interface.
R.W. Taylor
IEEE Conference on Artificial Intelligence Applications 1990
C.V. Apte, Robert Dionne, et al.
IBM J. Res. Dev
Soo Lee Ho, M.I. Schor
IEEE Conference on Artificial Intelligence Applications 1990
M. Karnaugh
IEEE Conference on Artificial Intelligence Applications 1990