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A framework for set-oriented computation in inductive logic programming and its application in generalizing inverse entailment. (English) Zbl 1134.68467

Kramer, Stefan (ed.) et al., Inductive logic programming. 15th international conference, ILP 2005, Bonn, Germany, August 10–13, 2005. Proceedings. Berlin: Springer (ISBN 3-540-28177-0/pbk). Lecture Notes in Computer Science 3625. Lecture Notes in Artificial Intelligence, 69-86 (2005).
Summary: We propose a new approach to Inductive Logic Programming that systematically exploits caching and offers a number of advantages over current systems. It avoids redundant computation, is more amenable to the use of set-oriented generation and evaluation of hypotheses, and allows relational DBMS technology to be more easily applied to ILP systems. Further, our approach opens up new avenues such as probabilistically scoring rules during search and the generation of probabilistic rules. As a first example of the benefits of our ILP framework, we propose a scheme for defining the hypothesis search space through Inverse Entailment using multiple example seeds.
For the entire collection see [Zbl 1087.68006].

MSC:

68T05 Learning and adaptive systems in artificial intelligence
68N17 Logic programming

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