KBMT Project

A Case Study in Knowledge-Based Machine Translation

Автор: Kenneth Goodman, Sergei Nirenburg

Език:

Корици: С меки корици

Издател: Morgan Kaufmann Publishers

Наличност: Външен склад

Изпращаме след 10-18 дни

66.04 € 129.16 лв

Machine translation of natural languages is one of the most complex and comprehensive applications o...

Информация за книгата

Автор

Kenneth Goodman, Sergei Nirenburg

Език

Английски език

Корици

Книга - С меки корици

Издадена

1991

страници

331

EAN

9781558601291

ISBN

1558601295

Enbook ID

04808979

Издател

Morgan Kaufmann Publishers

Теглоt

580

Размери

229 x 189 x 23

Пълно описание

Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system 'really does'. This book fills that need with a detailed case study of a KBMT system implemented at the Center for Machine Translation at Carnegie Mellon University. The research consists in part of the creation of a system for translation between English and Japanese. The corpora used in the project were manuals for installing and maintaining IBM personal computers (sponsorship by IBM, through its Tokyo Research Laboratory). Individual chapters in this book describe the interlingua texts used in knowledge-based machine translation, the grammar formalism embodied in the system, the grammars and lexicons and their roles in the translation process, the process of source language analysis, an augmentation module that interactively and automatically resolves ambiguities remaining after source language analysis, and the generator, which produces target language sentences. Detailed appendices illustrate the process from analysis through generation. This book is intended for developers, researchers and advanced students in natural language processing and computational linguistics, including all those who have an interest in machine translation and machine-aided translation.

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