Before revision:  This paper introduces a neural-symbolic learning framework, called Feed-Forward Neural-Symbolic Learner (FF-NSL), that integrates state-of-the-art ILP systems  based on the Answer Set semantics, with neural networks , in order to learn interpretable hypotheses from labelled unstructured data.
After revision:  To address this problem, this paper proposes a neural-symbolic learning framework, called Feed-Forward Neural-Symbolic Learner (FF-NSL), that integrates state-of-the-art ILP systems based on the Answer Set semantics, with neural networks , in order to learn interpretable hypotheses from labelled unstructured data.