Proceedings

Relational Learning for NLP using Linear Threshold Elements

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Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Natural Language Processing. Pages 911-918.

Abstract

We describe a coherent view of learning and reasoning with relational representations in the context of natural language processing. In particular, we discuss th e Neuroidal Architecture, Inductive Logic Programming and the SNoW system explaining the relationships among these, and thereby offer an explanation of the theoretical basis for the SNoW system. We suggest that extensions of this system along the lines suggested by the theory may provide new levels of scalability and functionality.

Roni Khardon, Dan Roth, and Leslie G. Valiant. 1999. Relational Learning for NLP using Linear Threshold Elements. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99. IJCAI, 911–918. https://ijcai.org/proceedings/1999/130
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