Treffer: KQML-Accessible, High-Performance, Massive Knowledge Bases.
Title:
KQML-Accessible, High-Performance, Massive Knowledge Bases.
Authors:
Contributors:
MARYLAND UNIV COLLEGE PARK DEPT OF COMPUTER SCIENCE
Source:
DTIC AND NTIS
Publication Year:
1995
Collection:
Defense Technical Information Center: DTIC Technical Reports database
Subject Terms:
Cybernetics, KNOWLEDGE BASED SYSTEMS, DATA BASES, ALGORITHMS, NEURAL NETS, OPTIMIZATION, SYSTEMS ENGINEERING, DATA MANAGEMENT, DISTRIBUTED DATA PROCESSING, COMPUTER COMMUNICATIONS, INTEROPERABILITY, PERFORMANCE(ENGINEERING), INPUT OUTPUT PROCESSING, PARALLEL PROCESSING, PARALLEL PROCESSORS, PATTERN RECOGNITION, SYSTEMS ANALYSIS, DATA LINKS, COMPILERS, C PROGRAMMING LANGUAGE, MIMID(MULTIPLE INSTRUCTION MULTIPLE DATA), SIMD(SINGLE INSTRUCTION MULTIPLE DATA), KQML(KNOWLEDGE QUERY AND MANIPULATION LANGUAGE)
Document Type:
Fachzeitschrift
text
File Description:
text/html
Language:
English
Availability:
Rights:
APPROVED FOR PUBLIC RELEASE
Accession Number:
edsbas.BAE77980
Database:
BASE
Weitere Informationen
We have begun porting the SIMD Parka system to more generic MIMD machines. The system has been recoded in C and supported using runtime optimization packages developed in the high performance computing laboratory at Maryland. New 'scanning' algorithms have been developed for inheritance and recognition inferences. These algorithms have been tested with both random networks and on a recoding of the ontology of the CYC knowledge base. Tests show that the new version is significantly faster than the SIMD system, and that it promises to scale well to knowledge bases orders of magnitude larger than CYC.