Connectionist, statistical, and symbolic approaches to learning for natural language processing /
"This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised se...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
[1996]
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| Series: | Lecture notes in computer science ;
1040. Lecture notes in computer science. Lecture notes in artificial intelligence. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Learning approaches for natural language processing / S. Wermter, E. Riloff and G. Scheler
- Separating learning and representation / N.E. Sharkey and A.J.C. Sharkey
- Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods / S. Lawrence, S. Fong and C.L. Giles
- Extracting rules for grammar recognition from Cascade-2 networks / R. Hayward, A. Tickle and J. Diederich
- Generating English plural determiners from semantic representations: a neural network learning approach / G. Scheler
- Knowledge acquisition in concept and document spaces by using self-organizing neural networks / W. Winiwarter, E. Schweighofer and D. Merkl
- Using hybrid connectionist learning for speech/language analysis / V. Weber and S. Wermter
- SKOPE: A connectionist/symbolic architecture of spoken Korean processing / G. Lee and J.-H. Lee.