Evaluation of rule processing strategies in expert databases

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - International Conference on Data Engineering
PublisherPubl by IEEE
Pages404-412
ISBN (Print)818621389
StatePublished - Apr 1991
Externally publishedYes

Conference

TitleProceedings of the 7th International Conference on Data Engineering
CityKobe, Jpn
Period8 - 12 April 1991

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.

Citation Format(s)

Evaluation of rule processing strategies in expert databases. / Segev, Arie; Zhao, J. Leon.

Proceedings - International Conference on Data Engineering. Publ by IEEE, 1991. p. 404-412.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)