• 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