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Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing Book

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing
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 pape, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing has a rating of 3 stars
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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 pape, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing
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  • Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing
  • Written by author Stefan Wermter
  • Published by Springer-Verlag New York, LLC, November 2007
  • 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 pape
  • 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 paper
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Book Categories

Authors

Learning approaches for natural language processing1
Separating learning and representation17
Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods33
Extracting rules for grammar recognition from Cascade-2 networks48
Generating English plural determiners from semantic representations: a neural network learning approach61
Knowledge acquisition in concept and document spaces by using self-organizing neural networks75
Using hybrid connectionist learning for speech/language analysis87
SKOPE: A connectionist/symbolic architecture of spoken Korean processing102
Integrating different learning approaches into a multilingual spoken language translation system
Learning language using genetic algorithms132
A statistical syntactic disambiguation program and what it learns146
Training stochastic grammars on semantical categories160
Learning restricted probabilistic link grammars173
Learning PP attachment from corpus statistics188
A minimum description length approach to grammar inference203
Automatic classification of dialog acts with semantic classification trees and polygrams217
Sample selection in natural language learning230
Learning information extraction patterns from examples246
Implications of an automatic lexical acquisition system261
Using learned extraction patterns for text classification275
Issues in inductive learning of domain-specific text extraction rules290
Applying machine learning to anaphora resolution302
Embedded machine learning systems for natural language processing: a general framework315
Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique329
Applying an existing machine learning algorithm to text categorization343
Comparative results on using inductive logic programming for corpus-based parser construction355
Learning the past tense of English verbs using inductive logic programming370
A dynamic approach to paradigm-driven analogy385
Can punctuation help learning?399
Using parsed corpora for circumventing parsing413
A symbolic and surgical acquisition of terms through variation425
A revision learner to acquire verb selection rules from human-made rules and examples439
Learning from texts - a terminological metareasoning perspective453


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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 pape, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing

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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 pape, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing

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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 pape, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing

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