Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science
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9783540609254, 9783540497387

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Training stochastic grammars on semantical categories

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_45 ◽

1996 ◽

pp. 160-172 ◽

Cited By ~ 1

Author(s):

Wide R. Hogenhout ◽

Yuji Matsumoto

Keyword(s):

Stochastic Grammars

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Extracting rules for grammar recognition from Cascade-2 networks

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_37 ◽

1996 ◽

pp. 48-60 ◽

Cited By ~ 1

Author(s):

Ross Hayward ◽

Alan Tickle ◽

Joachim Diederich

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Learning approaches for natural language processing

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_34 ◽

1996 ◽

pp. 1-16 ◽

Cited By ~ 2

Author(s):

Stefan Wermter ◽

Ellen Riloff ◽

Gabriele Scheler

Keyword(s):

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

Learning Approaches

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Knowledge acquisition in concept and document spaces by using self-organizing neural networks

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_39 ◽

1996 ◽

pp. 75-86 ◽

Cited By ~ 1

Author(s):

Werner Winiwarter ◽

Erich Schweighofer ◽

Dieter Merkl

Keyword(s):

Neural Networks ◽

Knowledge Acquisition ◽

Self Organizing

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A revision learner to acquire verb selection rules from human-made rules and examples

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_65 ◽

1996 ◽

pp. 439-452 ◽

Cited By ~ 1

Author(s):

Shigeo Kaneda ◽

Hussein Almuallim ◽

Yasuhiro Akiba ◽

Megumi Ishii ◽

Tsukasa Kawaoka

Keyword(s):

Selection Rules

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Using parsed corpora for circumventing parsing

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_63 ◽

1996 ◽

pp. 413-424

Author(s):

Aravind K. Joshi ◽

B. Srinivas

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Comparative results on using inductive logic programming for corpus-based parser construction

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_59 ◽

1996 ◽

pp. 355-369 ◽

Cited By ~ 5

Author(s):

John M. Zelle ◽

Raymond J. Mooney

Keyword(s):

Logic Programming ◽

Inductive Logic Programming ◽

Inductive Logic ◽

Comparative Results

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Issues in inductive learning of domain-specific text extraction rules

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_54 ◽

1996 ◽

pp. 290-301 ◽

Cited By ~ 4

Author(s):

Stephen Soderland ◽

David Fisher ◽

Jonathan Aseltine ◽

Wendy Lehnert

Keyword(s):

Inductive Learning ◽

Text Extraction ◽

Domain Specific

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Sample selection in natural language learning

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_50 ◽

1996 ◽

pp. 230-245 ◽

Cited By ~ 1

Author(s):

Sean P. Engelson ◽

Ido Dagan

Keyword(s):

Natural Language ◽

Language Learning ◽

Sample Selection ◽

Natural Language Learning

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Embedded machine learning systems for natural language processing: A general framework

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science ◽

10.1007/3-540-60925-3_56 ◽

1996 ◽

pp. 315-328 ◽

Cited By ~ 4

Author(s):

Claire Cardie

Keyword(s):

Machine Learning ◽

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

General Framework ◽

Learning Systems

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Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Training stochastic grammars on semantical categories

Extracting rules for grammar recognition from Cascade-2 networks

Learning approaches for natural language processing

Knowledge acquisition in concept and document spaces by using self-organizing neural networks

A revision learner to acquire verb selection rules from human-made rules and examples

Using parsed corpora for circumventing parsing

Comparative results on using inductive logic programming for corpus-based parser construction

Issues in inductive learning of domain-specific text extraction rules

Sample selection in natural language learning

Embedded machine learning systems for natural language processing: A general framework

Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing - Lecture Notes in Computer Science
Latest Publications