この論文をさがす
説明
This paper presents a general procedure for inverse entailment which constructs inductive hypotheses in inductive logic programming. Based on inverse entailment, not only unit clauses but also characteristic clauses are deduced from a background theory together with the negation of positive examples. Such clauses can be computed by a resolution method for consequence finding. Unlike previous work on inverse entailment, our proposed method called CF-induction is sound and complete for finding hypotheses from full clausal theories, and can be used for inducing not only definite clauses but also non-Horn clauses and integrity constraints. We also show that CF-induction can be used to compute abductive explanations, and then compare induction and abduction from the viewpoint of inverse entailment and consequence finding.
収録刊行物
-
- Machine Learning
-
Machine Learning 55 (2), 109-135, 2004-05
Springer Science and Business Media LLC
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1361418519991127424
-
- NII論文ID
- 30012262859
-
- ISSN
- 08856125
-
- データソース種別
-
- Crossref
- CiNii Articles
- OpenAIRE
