DocumentCode :
914300
Title :
Coupling production systems and database systems: a homogeneous approach
Author :
Sellis, Timos ; Lin, Chih-Chen ; Raschid, Louiqa
Author_Institution :
Maryland Univ., College Park, MD, USA
Volume :
5
Issue :
2
fYear :
1993
fDate :
4/1/1993 12:00:00 AM
Firstpage :
240
Lastpage :
256
Abstract :
Methods for storing and manipulating large rule bases using a relational database management systems (DBMS) are discussed. An approach to decomposing and storing the condition elements in the antecedents of rules such as those used in production rule-based systems is presented. A set-oriented approach, DBCond, which uses a special data structure that is implemented using relations is proposed. A matching algorithm for DBCond uses the relational structures to efficiently identify rules whose antecedents are satisfied. The performance of DBCond is compared with that of DBRete, a DBMS implementation of the Rete match algorithm developed for use with the production rule language OPS5. DBCond is also compared with DBQuery, a method that is based on evaluating queries corresponding to the conditions in the antecedents of the rules. Improvements to the data structure and the algorithms of the DBCond method are described. An advantage of DBCond is that it is fully parallelizable, thus making it attractive for parallel computing environments
Keywords :
deductive databases; knowledge based systems; relational databases; set theory; DBCond; DBMS implementation; DBQuery; DBRete; Rete match algorithm; condition elements; large rule bases; matching algorithm; parallel computing environments; parallelizable; production rule language OPS5; production rule-based systems; relational database management systems; relational structures; set-oriented approach; special data structure; Artificial intelligence; Data engineering; Data structures; Database systems; Knowledge based systems; Knowledge management; Manufacturing processes; Parallel processing; Production systems; Relational databases;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.219733
Filename :
219733
Link To Document :
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