ijcai 1996 论文列表
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing.
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Learning from texts - a terminological metareasoning perspective.
A revision learner to acquire verb selection rules from human-made rules and examples.
A symbolic and surgical acquisition of terms through variation.
Using parsed corpora for circumventing parsing.
Can punctuation help learning?
A dynamic approach to paradigm-driven analogy.
Learning the past tense of English verbs using inductive logic programming.
Comparative results on using inductive logic programming for corpus-based parser construction.
Applying an existing machine learning algorithm to text categorization.
Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique.
Embedded machine learning systems for natural language processing: a general framework.
Applying machine learning to anaphora resolution.
Issues in inductive learning of domain-specific text extraction rules.
Using learned extraction patterns for text classification.
Implications of an automatic lexical acquisition system.
Learning information extraction patterns from examples.
Sample selection in natural language learning.
Automatic classification of dialog acts with semantic classification trees and polygrams.
A minimum description length approach to grammar inference.
Learning PP attachment from corpus statistics.
Learning restricted probabilistic link grammars.
Training stochastic grammars on semantical categories.
A statistical syntactic disambiguation program and what it learns.
Learning language using genetic algorithms.
Integrating different learning approaches into a multilingual spoken language translation system.
SKOPE: A connectionist/symbolic architecture of spoken Korean processing.
Using hybrid connectionist learning for speech/language analysis.
Knowledge acquisition in concept and document spaces by using self-organizing neural networks.
Generating English plural determiners from semantic representations: a neural network learning approach.
Extracting rules for grammar recognition from Cascade-2 networks.
Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods.
Separating learning and representation.
Learning approaches for natural language processing.
