Grammars for Language and Genes Theoretical and Empirical Investigations /

Grammars are gaining importance in natural language processing and computational biology as a means of encoding theories and structuring algorithms. But one serious obstacle to applications of grammars is that formal language theory traditionally classifies grammars according to their weak generativ...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Chiang, David (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Colección:Theory and Applications of Natural Language Processing,
Temas:
Machine theory.
Natural language processing (Computer science).
Bioinformatics.
Formal Languages and Automata Theory.
Natural Language Processing (NLP).
Computational and Systems Biology.
Acceso en línea:Texto Completo

MARC

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100 1 |a Chiang, David.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Grammars for Language and Genes  |h [electronic resource] :  |b Theoretical and Empirical Investigations /  |c by David Chiang. 
250 |a 1st ed. 2012. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2012. 
300 |a XII, 120 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Theory and Applications of Natural Language Processing,  |x 2192-0338 
505 0 |a 1.Introduction -- 2.Foundation -- 3.Statistical Parsing -- 4.Machine Translation -- 5.Biological Sequence Analysis: Basics -- 6.Biological Sequence Analysis: Intersection -- 7.Conclusion -- References -- Index. 
520 |a Grammars are gaining importance in natural language processing and computational biology as a means of encoding theories and structuring algorithms. But one serious obstacle to applications of grammars is that formal language theory traditionally classifies grammars according to their weak generative capacity (what sets of strings they generate) and tends to ignore strong generative capacity (what sets of structural descriptions they generate) even though the latter is more relevant to applications. This book develops and demonstrates a framework for carrying out rigorous comparisons of grammar formalisms in terms of their usefulness for applications, focusing on three areas of application: statistical parsing, natural language translation, and biological sequence analysis. These results should pave the way for theoretical research to pursue results that are more directed towards applications, and for practical research to explore the use of advanced grammar formalisms more easily. 
650 0 |a Machine theory. 
650 0 |a Natural language processing (Computer science). 
650 0 |a Bioinformatics. 
650 1 4 |a Formal Languages and Automata Theory. 
650 2 4 |a Natural Language Processing (NLP). 
650 2 4 |a Computational and Systems Biology. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783642270802 
776 0 8 |i Printed edition:  |z 9783642204432 
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830 0 |a Theory and Applications of Natural Language Processing,  |x 2192-0338 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-642-20444-9  |z Texto Completo 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710) 

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