Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including word...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Zhiyuan [verfasserIn] |
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| Format: |
E-Book |
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| Sprache: |
Englisch |
| Erschienen: |
Erscheinungsort nicht ermittelbar: Springer Nature ; 2020 |
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| Rechteinformationen: |
Open Access Creative Commons ; by/4.0 |
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| Schlagwörter: |
Natural language & machine translation |
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| Umfang: |
1 Online-Ressource (334 p.) |
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| Links: | |
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| ISBN: |
978-981-15-5573-2 |
| Katalog-ID: |
1836429029 |
|---|
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| 520 | |a This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing | ||
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| 650 | 4 | |a Natural language and machine translation | |
| 650 | 4 | |a Computational and corpus linguistics | |
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| 700 | 1 | |a Sun, Maosong |4 oth | |
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9789811555732 978-981-15-5573-2 978 (DE-627)1836429029 (DE-599)KEP062167626 (OCoLC)1286318421 (OAPEN)39974 (EBP)062167626 DE-627 eng DE-627 rda eng UYQL bicssc CFX bicssc UYQ bicssc UNF bicssc Liu, Zhiyuan verfasserin aut Representation Learning for Natural Language Processing [Erscheinungsort nicht ermittelbar] Springer Nature 2020 1 Online-Ressource (334 p.) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Open Access Unrestricted online access star This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing Creative Commons by/4.0 cc English Natural language & machine translation Computational linguistics Artificial intelligence Data mining Natural language and machine translation Computational and corpus linguistics Lin, Yankai oth Sun, Maosong oth https://library.oapen.org/bitstream/id/9a6bb0ee-c88c-4cf6-9e63-84a3899a4d91/2020_Book_RepresentationLearningForNatur.pdf X:OAPEN Verlag OAPEN Library: download the publication kostenfrei https://library.oapen.org/handle/20.500.12657/39974 X:OAPEN Verlag OAPEN Library: description of the publication kostenfrei ZDB-94-OAL GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_31 ISIL_DE-27 GBV_ILN_34 ISIL_DE-18-302 GBV_ILN_39 ISIL_DE-547 GBV_ILN_40 ISIL_DE-7 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_65 ISIL_DE-3 GBV_ILN_70 ISIL_DE-89 GBV_ILN_72 ISIL_DE-35 GBV_ILN_95 ISIL_DE-542 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_136 ISIL_DE-Wis1 GBV_ILN_147 ISIL_DE-Fl3 GBV_ILN_161 ISIL_DE-960 GBV_ILN_187 ISIL_DE-Ki95 GBV_ILN_213 ISIL_DE-551 GBV_ILN_230 ISIL_DE-552 GBV_ILN_283 ISIL_DE-Ha163 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_603 ISIL_DE-B1556 GBV_ILN_808 GBV_ILN_2403 ISIL_DE-LFER BO 22 01 0018 4280087377 OLR-ZDB-94-OAL OAPEN Library zu 01-03-23 23 01 0830 4280639248 OLR-OAPEN f z 01-03-23 30 01 0104 428099952X GBV-OAPEN z 01-03-23 31 01 0027 4280282102 z 01-03-23 34 01 3551 427883764X OLR-OAPEN zi002 01-03-23 39 01 0547 4281190198 GBV-OAPEN ke 01-03-23 40 01 0007 4279906149 OLR-OAPEN xsn 01-03-23 63 01 3401 4281570500 E-Books LF GBV-OAPEN z 01-03-23 65 01 0003 4281814132 OLR-OAPEN z 01-03-23 70 01 0089 4280460302 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 72 01 0035 4278656440 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 95 01 3095 4343185664 OLR-OAL Vervielfältigungen (z.B. 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| spelling |
9789811555732 978-981-15-5573-2 978 (DE-627)1836429029 (DE-599)KEP062167626 (OCoLC)1286318421 (OAPEN)39974 (EBP)062167626 DE-627 eng DE-627 rda eng UYQL bicssc CFX bicssc UYQ bicssc UNF bicssc Liu, Zhiyuan verfasserin aut Representation Learning for Natural Language Processing [Erscheinungsort nicht ermittelbar] Springer Nature 2020 1 Online-Ressource (334 p.) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Open Access Unrestricted online access star This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing Creative Commons by/4.0 cc English Natural language & machine translation Computational linguistics Artificial intelligence Data mining Natural language and machine translation Computational and corpus linguistics Lin, Yankai oth Sun, Maosong oth https://library.oapen.org/bitstream/id/9a6bb0ee-c88c-4cf6-9e63-84a3899a4d91/2020_Book_RepresentationLearningForNatur.pdf X:OAPEN Verlag OAPEN Library: download the publication kostenfrei https://library.oapen.org/handle/20.500.12657/39974 X:OAPEN Verlag OAPEN Library: description of the publication kostenfrei ZDB-94-OAL GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_31 ISIL_DE-27 GBV_ILN_34 ISIL_DE-18-302 GBV_ILN_39 ISIL_DE-547 GBV_ILN_40 ISIL_DE-7 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_65 ISIL_DE-3 GBV_ILN_70 ISIL_DE-89 GBV_ILN_72 ISIL_DE-35 GBV_ILN_95 ISIL_DE-542 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_136 ISIL_DE-Wis1 GBV_ILN_147 ISIL_DE-Fl3 GBV_ILN_161 ISIL_DE-960 GBV_ILN_187 ISIL_DE-Ki95 GBV_ILN_213 ISIL_DE-551 GBV_ILN_230 ISIL_DE-552 GBV_ILN_283 ISIL_DE-Ha163 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_603 ISIL_DE-B1556 GBV_ILN_808 GBV_ILN_2403 ISIL_DE-LFER BO 22 01 0018 4280087377 OLR-ZDB-94-OAL OAPEN Library zu 01-03-23 23 01 0830 4280639248 OLR-OAPEN f z 01-03-23 30 01 0104 428099952X GBV-OAPEN z 01-03-23 31 01 0027 4280282102 z 01-03-23 34 01 3551 427883764X OLR-OAPEN zi002 01-03-23 39 01 0547 4281190198 GBV-OAPEN ke 01-03-23 40 01 0007 4279906149 OLR-OAPEN xsn 01-03-23 63 01 3401 4281570500 E-Books LF GBV-OAPEN z 01-03-23 65 01 0003 4281814132 OLR-OAPEN z 01-03-23 70 01 0089 4280460302 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 72 01 0035 4278656440 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 95 01 3095 4343185664 OLR-OAL Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 24-06-23 110 01 3110 4281375007 OLR-GBV-OAPEN Open Access z 01-03-23 136 01 3526 4279547211 OLR-OAPEN z 01-03-23 147 01 3528 4282019204 OLR-OAPEN frei verfügbar für Europa-Universität Flensburg, Hochschule Flensburg und Zentrale Hochschulbibliothek Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. 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| allfields_unstemmed |
9789811555732 978-981-15-5573-2 978 (DE-627)1836429029 (DE-599)KEP062167626 (OCoLC)1286318421 (OAPEN)39974 (EBP)062167626 DE-627 eng DE-627 rda eng UYQL bicssc CFX bicssc UYQ bicssc UNF bicssc Liu, Zhiyuan verfasserin aut Representation Learning for Natural Language Processing [Erscheinungsort nicht ermittelbar] Springer Nature 2020 1 Online-Ressource (334 p.) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Open Access Unrestricted online access star This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing Creative Commons by/4.0 cc English Natural language & machine translation Computational linguistics Artificial intelligence Data mining Natural language and machine translation Computational and corpus linguistics Lin, Yankai oth Sun, Maosong oth https://library.oapen.org/bitstream/id/9a6bb0ee-c88c-4cf6-9e63-84a3899a4d91/2020_Book_RepresentationLearningForNatur.pdf X:OAPEN Verlag OAPEN Library: download the publication kostenfrei https://library.oapen.org/handle/20.500.12657/39974 X:OAPEN Verlag OAPEN Library: description of the publication kostenfrei ZDB-94-OAL GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_31 ISIL_DE-27 GBV_ILN_34 ISIL_DE-18-302 GBV_ILN_39 ISIL_DE-547 GBV_ILN_40 ISIL_DE-7 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_65 ISIL_DE-3 GBV_ILN_70 ISIL_DE-89 GBV_ILN_72 ISIL_DE-35 GBV_ILN_95 ISIL_DE-542 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_136 ISIL_DE-Wis1 GBV_ILN_147 ISIL_DE-Fl3 GBV_ILN_161 ISIL_DE-960 GBV_ILN_187 ISIL_DE-Ki95 GBV_ILN_213 ISIL_DE-551 GBV_ILN_230 ISIL_DE-552 GBV_ILN_283 ISIL_DE-Ha163 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_603 ISIL_DE-B1556 GBV_ILN_808 GBV_ILN_2403 ISIL_DE-LFER BO 22 01 0018 4280087377 OLR-ZDB-94-OAL OAPEN Library zu 01-03-23 23 01 0830 4280639248 OLR-OAPEN f z 01-03-23 30 01 0104 428099952X GBV-OAPEN z 01-03-23 31 01 0027 4280282102 z 01-03-23 34 01 3551 427883764X OLR-OAPEN zi002 01-03-23 39 01 0547 4281190198 GBV-OAPEN ke 01-03-23 40 01 0007 4279906149 OLR-OAPEN xsn 01-03-23 63 01 3401 4281570500 E-Books LF GBV-OAPEN z 01-03-23 65 01 0003 4281814132 OLR-OAPEN z 01-03-23 70 01 0089 4280460302 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 72 01 0035 4278656440 OLR-OAPEN-OA OAPEN Online Library Open Access eBook z 01-03-23 95 01 3095 4343185664 OLR-OAL Vervielfältigungen (z.B. 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| allfieldsGer |
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7.012537 |