國立虎尾科技大學 |

Hybrid Approaches to Machine Translation

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Hybrid Approaches to Machine Translation/ edited by Marta R. Costa-jussà, Reinhard Rapp, Patrik Lambert, Kurt Eberle, Rafael E. Banchs, Bogdan Babych.
other author:	Costa-jussà, Marta R.
Description:	IX, 205 p. 45 illus., 18 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Natural language processing (Computer science). -
Online resource:	https://doi.org/10.1007/978-3-319-21311-8
ISBN:	9783319213118

Hybrid Approaches to Machine Translation
Hybrid Approaches to Machine Translation[electronic resource] /edited by Marta R. Costa-jussà, Reinhard Rapp, Patrik Lambert, Kurt Eberle, Rafael E. Banchs, Bogdan Babych. - 1st ed. 2016. - IX, 205 p. 45 illus., 18 illus. in color.online resource. - Theory and Applications of Natural Language Processing,2192-032X. - Theory and Applications of Natural Language Processing,.

Preface -- Foreword -- Chapter 1. Hybrid Machine Translation Overview -- Part 1: Adding Linguistics into SMT -- Chapter 2. Controllent Ascent: Imbuing Statistical MT with Linguistic knowledge -- Chapter 3. Hybrid Word Alignment -- Chapter 4. Syntax in SMT -- Part 2. Using Machine Learning in MT -- Chapter 5. Machine Learning in RBMT -- Chapter 6. Language-Independent Hybrid MT -- Part 3. Hybrid NLP tools useful for MT -- Chapter 7. Use of Dependency Parsers in MT -- Chapter 8. Word Sense Disambiguation in MT. .

This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also – in the wider fields of Computational Linguistics, Machine Learning and Data Mining – to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.

ISBN: 9783319213118

Standard No.: 10.1007/978-3-319-21311-8doiSubjects--Topical Terms:

802180
Natural language processing (Computer science).

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Hybrid Approaches to Machine Translation
LDR:02970nam a22004095i 4500 001 972292
003 DE-He213
005 20200630221757.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319213118 $9 978-3-319-21311-8
024 7 $a 10.1007/978-3-319-21311-8 $2 doi
035 $a 978-3-319-21311-8
050 4 $a QA76.9.N38
072 7 $a UYQL $2 bicssc
072 7 $a COM073000 $2 bisacsh
072 7 $a UYQL $2 thema
082 0 4 $a 006.35 $2 23
245 1 0 $a Hybrid Approaches to Machine Translation $h [electronic resource] / $c edited by Marta R. Costa-jussà, Reinhard Rapp, Patrik Lambert, Kurt Eberle, Rafael E. Banchs, Bogdan Babych.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a IX, 205 p. 45 illus., 18 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Theory and Applications of Natural Language Processing, $x 2192-032X
505 0 $a Preface -- Foreword -- Chapter 1. Hybrid Machine Translation Overview -- Part 1: Adding Linguistics into SMT -- Chapter 2. Controllent Ascent: Imbuing Statistical MT with Linguistic knowledge -- Chapter 3. Hybrid Word Alignment -- Chapter 4. Syntax in SMT -- Part 2. Using Machine Learning in MT -- Chapter 5. Machine Learning in RBMT -- Chapter 6. Language-Independent Hybrid MT -- Part 3. Hybrid NLP tools useful for MT -- Chapter 7. Use of Dependency Parsers in MT -- Chapter 8. Word Sense Disambiguation in MT. .
520 $a This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also – in the wider fields of Computational Linguistics, Machine Learning and Data Mining – to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.
650 0 $a Natural language processing (Computer science). $3 802180
650 0 $a Computational linguistics. $3 555811
650 0 $a Translation and interpretation. $3 1256633
650 1 4 $a Natural Language Processing (NLP). $3 1254293
650 2 4 $a Computational Linguistics. $3 670080
650 2 4 $a Translation. $3 796482
700 1 $a Costa-jussà, Marta R. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1267481
700 1 $a Rapp, Reinhard. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1064262
700 1 $a Lambert, Patrik. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1267482
700 1 $a Eberle, Kurt. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1267483
700 1 $a Banchs, Rafael E. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 981871
700 1 $a Babych, Bogdan. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1267484
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319213101
776 0 8 $i Printed edition: $z 9783319213125
776 0 8 $i Printed edition: $z 9783319793344
830 0 $a Theory and Applications of Natural Language Processing, $x 2192-032X $3 1254778
856 4 0 $u https://doi.org/10.1007/978-3-319-21311-8
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)