リテラル連関とMDL基準による相対最小汎化の計算法

抄録

This paper proposes a computation method of relative least general generalization using liteal association and MDL criteria in inductive inferene with a logical framework. The method does not require additional conditions, which are difncult to be described in KDD applications, to select relevant ground atoms from background knowledge. The notion literal association is a relationship among literals through common variables in the literals. The MDL criteria selects literals in the generalized clause by the description length of literals as a post-processing. The search using these properties is processed with constraints that the generalization covers no negative examples in top-down manner. The validity of the proposed method is shown by an experiment to learn list processing predicates from examples in logic programming traditions.