Machine translation: a knowledge-based approach
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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1 .5.2 Nature and Size of Knowledge Bases Knowledge-based machine
translation must be supported by world ... flow of reference data between the
various data repositories ("static knowledge sources") and the various processing
One such structure involves the blackboard mode of control, in which a number of
processes (known as dynamic knowledge sources) post their findings and obtain
their decision knowledge from a set of public data structures called ...
Knowledge-Based Machine Translation (KBMT) The process of analysis (q. v.) of
a source language (q. v.) text, augmentation (q. v.) if necessary, and generation (
q.v.) into a target language O7.v.) text, using all required knowledge sources ...
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Treatment of Meaning in MT Systems
The Concept of Interlingua
Lexicography and Knowledge Acquisition
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Grading Knowledge: Extracting Degree Information from Texts, Issue 1744
No preview available - 1999