This paper investigates a way of using background knowledge in the rule discovery process. This technique is based on Generalization Distribution Table (GDT for short), in which the probabilistic relationships between concepts and instances over discrete domains are represented. We describe how to use background knowledge as a bias to adjust the prior distribution so that the better knowledge can be discovered.
展开▼
机译：本文研究了一种在规则发现过程中使用背景知识的方法。该技术基于通用分布表（Generalized Distribution Table，简称GDT），其中表示了概念和实例在离散域之间的概率关系。我们描述了如何使用背景知识作为调整先验分布的偏见，以便可以发现更好的知识。
展开▼
