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