大葉大學圖書館 |

Hybrid approaches to machine translation[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.35
書名/作者:	Hybrid approaches to machine translation/ edited by Marta R. Costa-jussa ... [et al.].
其他作者:	Costa-jussa, Marta R.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	ix, 205 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Natural language processing (Computer science)
標題:	Machine translating.
標題:	Computer Science.
標題:	Language Translation and Linguistics.
標題:	Computational Linguistics.
標題:	Translation.
ISBN:	9783319213118
ISBN:	9783319213101
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-21311-8

Hybrid approaches to machine translation[electronic resource] /
Hybrid approaches to machine translation[electronic resource] /edited by Marta R. Costa-jussa ... [et al.]. - Cham :Springer International Publishing :2016. - ix, 205 p. :ill. (some col.), digital ;24 cm. - 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:

411876
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Hybrid approaches to machine translation[electronic resource] /
LDR:02496nmm a2200325 a 4500 001 462012
003 DE-He213
005 20161214171830.0
006 m d
007 cr nn 008maaau
008 170223s2016 gw s 0 eng d
020 $a 9783319213118 $q (electronic bk.)
020 $a 9783319213101 $q (paper)
024 7 $a 10.1007/978-3-319-21311-8 $2 doi
035 $a 978-3-319-21311-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N38
072 7 $a UYQL $2 bicssc
072 7 $a COM042000 $2 bisacsh
082 0 4 $a 006.35 $2 23
090 $a QA76.9.N38 $b H992 2016
245 0 0 $a Hybrid approaches to machine translation $h [electronic resource] / $c edited by Marta R. Costa-jussa ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a ix, 205 p. : $b ill. (some col.), digital ; $c 24 cm.
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 411876
650 0 $a Machine translating. $3 607254
650 1 4 $a Computer Science. $3 423143
650 2 4 $a Language Translation and Linguistics. $3 463479
650 2 4 $a Computational Linguistics. $3 464721
650 2 4 $a Translation. $3 606399
700 1 $a Costa-jussa, Marta R. $3 666231
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a Theory and applications of natural language processing. $3 463477
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-21311-8
950 $a Computer Science (Springer-11645)