Rule activation techniques in active database systems

作者:Arie Segev, J. Leon Zhao

摘要

Efficient activation of rules is a fundamental issue in active database systems; choosing the suitable rule activation technique is therefore an important task. We have developed a technique, called join pattern indexing, to support incremental update of rule-derived data. In this paper, we compare join pattern indexing with discrimination networks (Rete and TREAT) for data-derivation rules. A performance study based on a stochastic model indicates that join pattern indexing is more efficient than discrimination networks in many cases.

论文关键词:active database systems, discrimination networks, join pattern indexing, intelligent database systems, rule triggering

论文评审过程:

论文官网地址:https://doi.org/10.1007/BF00127781