Title
Extending a primary-memory-based terminological reasoning system with database capabilities
Keywords
Artificial intelligence; Database systems; Knowledge-based systems; Selective inheritance
Abstract
New applications in engineering, science, and office automation require large knowledge bases and efficient reasoning capabilities. The traditional AI systems lack the means to support large knowledge bases, and the traditional database systems lack the capability for knowledge reasoning. This has resulted in efforts to integrate the capabilities of database and AI systems. This paper discusses how an existing primary-memory-based knowledge representation and comprehension system, known as Snowy, has been extended with database capabilities. The overall architecture of the resulting system, called Snowy-KBMS, is presented. The system design, operations, and an efficient search mechanism are discussed in detail.
Publication Date
12-1-1998
Publication Title
International Journal of Computers and Applications
Volume
20
Issue
2
Number of Pages
61-67
Document Type
Article
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0031617610 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0031617610
STARS Citation
Salimi, A.; Gomez, F.; and Orooji, A., "Extending a primary-memory-based terminological reasoning system with database capabilities" (1998). Scopus Export 1990s. 3748.
https://stars.library.ucf.edu/scopus1990/3748