DocumentCode
3202706
Title
Evaluation of rule processing strategies in expert databases
Author
Segev, Arie ; Zhao, J. Leon
Author_Institution
Haas Sch. of Bus., California Univ., Berkeley, CA, USA
fYear
1991
fDate
8-12 Apr 1991
Firstpage
404
Lastpage
412
Abstract
Rule processing strategies in expert database systems which involve rules conditional on join results of base relations are studied. In particular, those rules that require very fast response time in their evaluation are considered. It is proposed to materialize the results of firing a rule in a relation, the rule relation. Performance evaluation of several strategies shows that under the clustered B-trees, strategies using pattern relations perform better than those without pattern relations. The strategy with skinny pattern relations performs poorly in comparison to that with bulky pattern relations. The selective bulky pattern strategy performs better than the bulky pattern strategy. The selective pattern strategy outperforms other strategies in terms of expected total cost. However, it always uses more storage space than the direct materialization
Keywords
database management systems; expert systems; performance evaluation; trees (mathematics); base relations; clustered B-trees; expert databases; join results; pattern relations; performance evaluation; rule processing strategies; rule relation; Costs; Database systems; Decision support systems; Delay; Expert systems; Firing; Material storage; Production planning; Production systems; Query processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 1991. Proceedings. Seventh International Conference on
Conference_Location
Kobe
Print_ISBN
0-8186-2138-9
Type
conf
DOI
10.1109/ICDE.1991.131489
Filename
131489
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