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June 17, 1995
Organizers: Stephen Muggleton, Fumio Mizoguchi, Koichi Furukawa
Inductive logic programming is a new research topics expanding rapidly on the intersection of logic programming and machine learning. It deals with supervised learning which produces a discrimination function to separate positive examples from negative examples. It is an extention of propositional logic based supervised machine learning systems such as ID3. The merit of the new approach is the capability of utilizing background knowledge related to the concept to be learned.
The workshop stresses special attentions to the contribution of logic programming to machine learning as well as the opposite. It stresses also to applications of ILP technologies to a wide variety of problems. Any topics related to ILP are also welcome.
Papers should be sent to Fumio Mizoguchi either by email or by mail. The dead line of paper submission is April 15. The aceptance of papers will be notified by May 1. Camera ready should be sent by May 15.
Copyright © Sat May 16 23:20:25 2009 by Michael Ley (ley@uni-trier.de)