Relational Learning for NLP using Linear Threshold Elements
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
Khardon, R., Roth, D., & Valiant, L. G. (1999). Relational Learning for NLP using Linear Threshold Elements. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 (pp. 911–918). IJCAI. https://ijcai.org/proceedings/1999/130
@inproceedings{ijcai1999p130,
title = {Relational Learning for NLP using Linear Threshold Elements},
author = {Khardon, Roni and Roth, Dan and Valiant, Leslie G.},
booktitle = {Proceedings of the Sixteenth International Joint Conference on
Artificial Intelligence, {IJCAI-99}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Thomas Dean},
pages = {911--918},
year = {1999},
note = {Natural Language Processing},
url = {https://ijcai.org/proceedings/1999/130},
}
TY - CPAPER TI - Relational Learning for NLP using Linear Threshold Elements AU - Khardon, Roni AU - Roth, Dan AU - Valiant, Leslie G. T2 - Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 PB - International Joint Conferences on Artificial Intelligence PY - 1999 SP - 911 EP - 918 UR - https://ijcai.org/proceedings/1999/130 ER -Copied
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