摘要
Two contributions are sketched. A first contribution shows that a special case of relational learning can be transformed into attribute-value learning. However, it is much more tractable to stick to the relational representation than to apply the sketched transformation. This provides a sound theoretical justification for inductive logic programming. In a second contribution, we show how existing attribute-value learning techniques and systems can be upgraded towards inductive logic programming using the ‘Leuven’ methodology and illustrate it using the Claudien, Tilde, ICL, Warmr, TIC, MacCent and RRL systems.
摘要译文
两个部分草稿。第一个贡献表明，关系学习的一个特例可以转化为属性 - 价值学习。但是，坚持关系表示比应用草图变换要容易得多。这为归纳逻辑编程提供了合理的理论依据。在第二个贡献中，我们展示了现有的属性值学习技术和系统如何使用“鲁汶”方法升级为归纳逻辑编程，并使用Claudien，Tilde，ICL，Warmr，TIC，MacCent和RRL系统进行说明。
Luc De Raedt1. Attribute-value learning versus inductive logic programming: The missing links. Inductive Logic Programming[M].DE: Springer, 1998: 1-8