SARDSRN: A Neural Network Shift-Reduce Parser
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Machine Learning. Pages 820-826.
Abstract
Simple Recurrent Networks (SRNs) have been widely used in natural language tasks. SARDSRN extends the SRN by explicitly representing the input sequence in a SARDNET self-organizing map. The distributed SRN component leads to good generalization and robust cognitive properties, whereas the SARDNET map provides exact representations of the sentence constituents. This combination allows SARDSRN to learn to parse sentences with more complicated structure than can the SRN alone, and suggests that the approach could scale up to realistic natural language.
@inproceedings{ijcai1999p117,
title = {SARDSRN: A Neural Network Shift-Reduce Parser},
author = {Mayberry, Marshall R. and Miikkulainen, Risto},
booktitle = {Proceedings of the Sixteenth International Joint Conference on
Artificial Intelligence, {IJCAI-99}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Thomas Dean},
pages = {820--826},
year = {1999},
note = {Machine Learning},
url = {https://ijcai.org/proceedings/1999/117},
}
TY - CPAPER TI - SARDSRN: A Neural Network Shift-Reduce Parser AU - Mayberry, Marshall R. AU - Miikkulainen, Risto T2 - Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 PB - International Joint Conferences on Artificial Intelligence PY - 1999 SP - 820 EP - 826 UR - https://ijcai.org/proceedings/1999/117 ER -Copied
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