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Semantic Scholar14. IJCAI 1995: Montréal, Québec, Canada - Learning for Natural Language Processing
Stefan Wermter, Ellen Riloff, Gabriele Scheler:
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing. Lecture Notes in Computer Science 1040, Springer 1996, ISBN 3-540-60925-3- Stefan Wermter, Ellen Riloff, Gabriele Scheler:
Learning approaches for natural language processing. 1-16
Connectionist Networks and Hybrid Approaches
- Steve Lawrence, Sandiway Fong, C. Lee Giles:
Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods. 33-47 - Ross Hayward, Alan B. Tickle, Joachim Diederich:
Extracting rules for grammar recognition from Cascade-2 networks. 48-60 - Gabriele Scheler:
Generating English plural determiners from semantic representations: a neural network learning approach. 61-74 - Werner Winiwarter, Erich Schweighofer, Dieter Merkl:
Knowledge acquisition in concept and document spaces by using self-organizing neural networks. 75-86 - Volker Weber, Stefan Wermter:
Using hybrid connectionist learning for speech/language analysis. 87-101 - Gary Geunbae Lee, Jong-Hyeok Lee:
SKOPE: A connectionist/symbolic architecture of spoken Korean processing. 102-116 - Petra Geutner, Bernhard Suhm, Finn Dag Buø, Thomas Kemp, Laura Mayfield, Arthur E. McNair, Ivica Rogina, Tanja Schultz, Tilo Sloboda, Wayne H. Ward, Monika Woszczyna, Alex Waibel:
Integrating different learning approaches into a multilingual spoken language translation system. 117-131
Statistical Approaches
- Murat Ersan, Eugene Charniak:
A statistical syntactic disambiguation program and what it learns. 146-159 - Marion Mast, Heinrich Niemann, Elmar Nöth, Ernst Günter Schukat-Talamazzini:
Automatic classification of dialog acts with semantic classification trees and polygrams. 217-229
Symbolic Approaches
- Stephen Soderland, David Fisher, Jonathan Aseltine, Wendy G. Lehnert:
Issues in inductive learning of domain-specific text extraction rules. 290-301 - Claire Cardie:
Embedded machine learning systems for natural language processing: a general framework. 315-328 - Takefumi Yamazaki, Michael J. Pazzani, Christopher J. Merz:
Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique. 329-342 - Isabelle Moulinier, Jean-Gabriel Ganascia:
Applying an existing machine learning algorithm to text categorization. 343-354 - John M. Zelle, Raymond J. Mooney:
Comparative results on using inductive logic programming for corpus-based parser construction. 355-369 - Raymond J. Mooney, Mary Elaine Califf:
Learning the past tense of English verbs using inductive logic programming. 370-384 - Stefano Federici, Vito Pirrelli, François Yvon:
A dynamic approach to paradigm-driven analogy. 385-398 - Shigeo Kaneda, Hussein Almuallim, Yasuhiro Akiba, Megumi Ishii, Tsukasa Kawaoka:
A revision learner to acquire verb selection rules from human-made rules and examples. 439-452 - Udo Hahn, Manfred Klenner, Klemens Schnattinger:
Learning from texts - a terminological metareasoning perspective. 453-468
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