Machine Translation by Thierry Poibeau: New

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eBay 物品編號:404802467735

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物品狀況
很好: ...
Pages
296
Publication Date
2017-09-15
Subject Area
Software Development
Book Title
Machine Translation
Subject
Computer Science, Translation
ISBN
9780262534215
類別

關於產品

Product Identifiers

Publisher
MIT Press
ISBN-10
0262534215
ISBN-13
9780262534215
eBay Product ID (ePID)
234113651

Product Key Features

Number of Pages
296 Pages
Publication Name
Machine Translation
Language
English
Subject
Information Theory, Intelligence (Ai) & Semantics, Linguistics / General
Publication Year
2017
Type
Textbook
Subject Area
Computers, Language Arts & Disciplines
Author
Thierry Poibeau
Series
The MIT Press Essential Knowledge Ser.
Format
Trade Paperback

Dimensions

Item Height
0.6 in
Item Weight
9.4 Oz
Item Length
7 in
Item Width
5 in

Additional Product Features

Intended Audience
Trade
LCCN
2017-002546
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
418.020285635
Synopsis
A concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and major players in the industry. The dream of a universal translation device goes back many decades, long before Douglas Adams's fictional Babel fish provided this service in The Hitchhiker's Guide to the Galaxy . Since the advent of computers, research has focused on the design of digital machine translation tools-computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details. The book begins by discussing problems that must be solved during the development of a machine translation system and offering a brief overview of the evolution of the field. It then takes up the history of machine translation in more detail, describing its pre-digital beginnings, rule-based approaches, the 1966 ALPAC (Automatic Language Processing Advisory Committee) report and its consequences, the advent of parallel corpora, the example-based paradigm, the statistical paradigm, the segment-based approach, the introduction of more linguistic knowledge into the systems, and the latest approaches based on deep learning. Finally, it considers evaluation challenges and the commercial status of the field, including activities by such major players as Google and Systran., A concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and major players in the industry. The dream of a universal translation device goes back many decades, long before Douglas Adams's fictional Babel fish provided this service in The Hitchhiker's Guide to the Galaxy . Since the advent of computers, research has focused on the design of digital machine translation tools--computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details. The book begins by discussing problems that must be solved during the development of a machine translation system and offering a brief overview of the evolution of the field. It then takes up the history of machine translation in more detail, describing its pre-digital beginnings, rule-based approaches, the 1966 ALPAC (Automatic Language Processing Advisory Committee) report and its consequences, the advent of parallel corpora, the example-based paradigm, the statistical paradigm, the segment-based approach, the introduction of more linguistic knowledge into the systems, and the latest approaches based on deep learning. Finally, it considers evaluation challenges and the commercial status of the field, including activities by such major players as Google and Systran.
LC Classification Number
P308.P65 2017

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