Induction of logical relations based on specific generalization of strings
| Autor: | Ilyas Cicekli, Yasin Uzun |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Theoretical computer science
Background knowledge (BK) business.industry Generalization Computer science Inductive bias Communication Information science Statistical relational learning Inductive Logic Programming (ILP) Multi-task learning First orders Computer programming Logic programming Inductive programming Education Information management Inductive transfer Inductive logic programming International symposium Artificial intelligence Logical relations business Cybernetics |
| Zdroj: | 22nd International Symposium on Computer and Information Sciences, ISCIS 2007-Proceedings |
| DOI: | 10.1109/iscis.2007.4456855 |
| Popis: | Date of Conference: 7-9 Nov. 2007 Conference name: 22nd international symposium on computer and information sciences, 2007 Learning logical relations from examples expressed as first order facts has been studied extensively by the Inductive Logic Programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge. ©2007 IEEE. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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