Flattening and Saturation: Two Representation Changes for Generalization
作者:Céline Rouveirol
摘要
Two representation changes are presented: the first one, called flattening, transforms a first-order logic program with function symbols into an equivalent logic program without function symbols; the second one, called saturation, completes an example description with relevant information with respect to both the example and available background knowledge. The properties of these two represenlation changes are analyzed as well as their influence on a generalization algorithm that takes a single example as input.
论文关键词:Inductive logic programming, generalization with background knowledge
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论文官网地址:https://doi.org/10.1023/A:1022678217288