Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing (Paperback)

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