Category:LNCS 1040
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Lecture Notes in Computer Science, Volume 1040
Articles in category "LNCS 1040"
There are 33 articles in this category.
A
A connectionistslash symbolic architecture of spoken Korean processing
A dynamic approach to paradigm-driven analogy
A minimum description length approach to grammar inference
A revision learner to acquire verb selection rules from human-made rules and examples
A statistical syntactic disambiguation program and what it learns
A symbolic and surgical acquisition of terms through variation
Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique
Applying an existing machine learning algorithm to text categorization
Applying machine learning to anaphora resolution
Automatic classification of dialog acts with semantic classification trees and polygrams
C
Can punctuation help learning?
C cont.
Comparative, results on using inductive logic programming for corpus-based parser construction
E
Embedded machine learning systems for natural language processing: a general framework
Extracting rules for grammar recognition from Cascade-2 networks
G
Generating English plural determiners from semantic representations: a neural network learning approach
I
Implications of an automatic lexical acquisition system
Integrating different learning approaches into a multilingual spoken language translation system
Issues in inductive learning of domain-specific text extraction rules
K
Knowledge acquisition in concept and document spaces by using self-organizing neural networks
L
Learning PP attachment from corpus statistics
Learning approaches for natural language processing
Learning from texts - a terminological metareasoning perspective
Learning information extraction patterns from examples
L cont.
Learning language using genetic algorithms
Learning restricted probabilistic link grammars
Learning the past tense of English verbs using inductive logic programming
N
Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods
S
Sample selection in natural language learning
Separating learning and representation
T
Training stochastic grammars on semantical categories
U
Using hybrid connectionist learning for speechslash language analysis
Using learned extraction patterns for text classification
Using parsed corpora for circumventing parsing
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