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
Link To Document :
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