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The Design of Interpreters, Compilers, and Editors for Augmented Transition Networks (Symbolic computation/Artificial Intelligence) - Tapa dura

 
9783540127895: The Design of Interpreters, Compilers, and Editors for Augmented Transition Networks (Symbolic computation/Artificial Intelligence)

Sinopsis

Augmented Transition Network Grammars are at present the most widely used method for analyzing natural languages. Despite the increasing po- pularity of this method, however, no extensive papers on ATN-Grammars have been presented which would be accessible to a larger number of per- sons engaged in the problem from both the theoretical and practical points of view. Augmented Transition Networks (ATN) are derived from state automata. Like a finite state automaton, an ATN consists of a collection of la- beled states and arcs, a distinguished start state and a set of distin- guished final states. States are connected with each other by arcs crea- ting a directed graph or net. The label on an arc indicates a terminal symbol (word) or the type of words which must occur in an input stream to allow the transition to the next state. It is said that a sequence of words (or sentence) is accepted by such a net if there exists a se- quence of arcs (usually called a path), connecting the start state with a final state, which can be followed to the sentence. The finite state automaton is then enriched by several facilities which increase its computational power. The most important of them permits some arcs to be labeled by nonterminal rather than terminal symbols. This means that the transition through such an arc is actually the re- cursive application of the net beginning with a pointed state.

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Reseña del editor

Augmented Transition Network Grammars are at present the most widely used method for analyzing natural languages. Despite the increasing po­ pularity of this method, however, no extensive papers on ATN-Grammars have been presented which would be accessible to a larger number of per­ sons engaged in the problem from both the theoretical and practical points of view. Augmented Transition Networks (ATN) are derived from state automata. Like a finite state automaton, an ATN consists of a collection of la­ beled states and arcs, a distinguished start state and a set of distin­ guished final states. States are connected with each other by arcs crea­ ting a directed graph or net. The label on an arc indicates a terminal symbol (word) or the type of words which must occur in an input stream to allow the transition to the next state. It is said that a sequence of words (or sentence) is accepted by such a net if there exists a se­ quence of arcs (usually called a path), connecting the start state with a final state, which can be followed to the sentence. The finite state automaton is then enriched by several facilities which increase its computational power. The most important of them permits some arcs to be labeled by nonterminal rather than terminal symbols. This means that the transition through such an arc is actually the re­ cursive application of the net beginning with a pointed state.

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Condición: Bien
214 p: 72 Fig.
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9783642821240: The Design of Interpreters, Compilers, and Editors for Augmented Transition Networks (Artificial Intelligence)

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ISBN 10:  3642821243 ISBN 13:  9783642821240
Editorial: Springer, 2011
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BOLC, Leonard (ed)
Publicado por Springer Verlag, Berlin, 1983
ISBN 10: 3540127895 ISBN 13: 9783540127895
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Librería: HJP VERSANDBUCHHANDLUNG, WEDEL, SH, Alemania

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Library Binding. Condición: Good. 1st Edition. 214 p: 72 Fig. Nº de ref. del artículo: DSY-0340

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Imagen de archivo

Leonard Bolc
Publicado por Springer, 1983
ISBN 10: 3540127895 ISBN 13: 9783540127895
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Librería: BookHolders, Towson, MD, Estados Unidos de America

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: Reprint ] Publisher: Springer-Verlag Pub Date: 8/1/1983 Binding: Hardcover Pages: 214 Reprint edition. Nº de ref. del artículo: 6904640

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