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首页> 外文期刊>IEEE Transactions on Knowledge and Data Engineering >Rule ordering in bottom-up fixpoint evaluation of logic programs
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Rule ordering in bottom-up fixpoint evaluation of logic programs

机译:自底向上定点逻辑程序评估中的规则排序

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摘要

Logic programs can be evaluated bottom-up by repeatedly applying all rules, in "iterations", until the fixpoint is reached. However, it is often desirable-and, in some cases, e.g. programs with stratified negation, it is even necessary to guarantee the semantics-to apply the rules in some order. We present two algorithms that apply rules in a specified order without repeating inferences. One of them (GSN) is capable of dealing with a wide range of rule orderings, but with a little more overhead than the well-known seminaive algorithm (which we call BSN). The other (PSN) handles a smaller class of rule orderings, but with no overheads beyond those in BSN. We also demonstrate that by choosing a good ordering, we can reduce the number of rule applications (and thus the number of joins). We present a theoretical analysis of rule orderings and identify orderings that minimize the number of rule applications (for all possible instances of the base relations) with respect to a class of orderings called fair orderings. We also show that though nonfair orderings may do a little better on some data sets, they can do much worse on others. The analysis is supplemented by performance results.
机译:可以通过重复应用“迭代”中的所有规则,直到到达固定点,来自底向上评估逻辑程序。但是,这通常是理想的-在某些情况下,例如对于带有分层否定的程序,甚至有必要保证语义-以一定顺序应用规则。我们提出了两种算法,它们以指定的顺序应用规则而无需重复推理。其中之一(GSN)能够处理各种规则排序,但比众所周知的Seminaive算法(我们称为BSN)要多一些开销。另一个(PSN)处理的规则排序类别较小,但没有BSN中的开销。我们还演示了通过选择一个好的顺序,我们可以减少规则应用程序的数量(从而减少连接的数量)。我们对规则排序进行了理论分析,并确定了相对于称为“公平排序”的一类排序,可将规则应用数量(对于基本关系的所有可能实例)最小化的排序。我们还表明,尽管不公平的排序在某些数据集上可能会好一些,但在其他数据集上却可能差很多。性能结果将对分析进行补充。

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