Machine translation: a knowledge-based approach

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Morgan Kaufmann Publishers, 1992 - Computers - 258 pages
This is the first book devoted exclusively to knowledge-based machine translation. While most approaches to the machine translation for natural languages seek ways to translate source language texts into target language texts without full understanding of the text, knowledge-based machine translation is based on extracting and representing the meaning of the source text. It is scientifically the most challenging approach to the task of machine translation, and significant progress has been achieved within it in recent years.

The authors introduce the general paradigm of knowledge-based MT, survey major recent developments, compare it with other approaches and present a paradigmatic view of its component processes

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Treatment of Meaning in MT Systems
The Concept of Interlingua
Lexicography and Knowledge Acquisition

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About the author (1992)

Sergei Nirenburg is Professor of Computer Science and Electrical Engineering at University of Maryland, Baltimore County.

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