Graph Learning and Network Science for Natural Language Processing:
Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based...
Gespeichert in:
| Weitere beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Boca Raton, FL
CRC Press
2023
|
| Schriftenreihe: | Computational intelligence techniques
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781000789508/?ar |
| Zusammenfassung: | Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning. |
| Beschreibung: | Description based on online resource; title from digital title page (viewed on February 08, 2023) |
| Umfang: | 1 Online-Ressource. |
| ISBN: | 9781000789300 1000789306 9781003272649 1003272649 1000789500 9781000789508 |
Internformat
MARC
| LEADER | 00000nam a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-102560358 | ||
| 003 | DE-627-1 | ||
| 005 | 20240429114541.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240429s2023 xx |||||o 00| ||eng c | ||
| 020 | |a 9781000789300 |c electronic book |9 978-1-000-78930-0 | ||
| 020 | |a 1000789306 |c electronic book |9 1-000-78930-6 | ||
| 020 | |a 9781003272649 |c electronic book |9 978-1-003-27264-9 | ||
| 020 | |a 1003272649 |c electronic book |9 1-003-27264-9 | ||
| 020 | |a 1000789500 |c electronic book |9 1-000-78950-0 | ||
| 020 | |a 9781000789508 |c electronic book |9 978-1-000-78950-8 | ||
| 035 | |a (DE-627-1)102560358 | ||
| 035 | |a (DE-599)KEP102560358 | ||
| 035 | |a (ORHE)9781000789508 | ||
| 035 | |a (DE-627-1)102560358 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 072 | 7 | |a BUS |2 bisacsh | |
| 072 | 7 | |a COM |2 bisacsh | |
| 072 | 7 | |a COM |2 bisacsh | |
| 072 | 7 | |a UB |2 bicssc | |
| 082 | 0 | |a 006.35 |2 23 | |
| 245 | 1 | 0 | |a Graph Learning and Network Science for Natural Language Processing |c edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad |
| 264 | 1 | |a Boca Raton, FL |b CRC Press |c 2023 | |
| 264 | 4 | |c ©2023 | |
| 300 | |a 1 Online-Ressource. | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 490 | 0 | |a Computational intelligence techniques | |
| 500 | |a Description based on online resource; title from digital title page (viewed on February 08, 2023) | ||
| 520 | |a Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning. | ||
| 650 | 0 | |a Natural language processing (Computer science) | |
| 650 | 0 | |a Graph theory | |
| 650 | 0 | |a System analysis | |
| 650 | 4 | |a Traitement automatique des langues naturelles | |
| 650 | 4 | |a Analyse de systèmes | |
| 650 | 4 | |a systems analysis | |
| 650 | 4 | |a BUSINESS & ECONOMICS / Statistics | |
| 650 | 4 | |a COMPUTERS / Database Management / Data Mining | |
| 650 | 4 | |a COMPUTERS / Machine Theory | |
| 650 | 4 | |a Graph theory | |
| 650 | 4 | |a Natural language processing (Computer science) | |
| 650 | 4 | |a System analysis | |
| 700 | 1 | |a Garg, Muskan |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Gupta, Amit Kumar |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Prasad, Rajesh |e HerausgeberIn |4 edt | |
| 776 | 1 | |z 9781000789508 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781000789508 |
| 966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781000789508/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-102560358 |
|---|---|
| _version_ | 1821494933482110976 |
| adam_text | |
| any_adam_object | |
| author2 | Garg, Muskan Gupta, Amit Kumar Prasad, Rajesh |
| author2_role | edt edt edt |
| author2_variant | m g mg a k g ak akg r p rp |
| author_facet | Garg, Muskan Gupta, Amit Kumar Prasad, Rajesh |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)102560358 (DE-599)KEP102560358 (ORHE)9781000789508 |
| dewey-full | 006.35 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.35 |
| dewey-search | 006.35 |
| dewey-sort | 16.35 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03491nam a22006492 4500</leader><controlfield tag="001">ZDB-30-ORH-102560358</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240429114541.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240429s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781000789300</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-000-78930-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1000789306</subfield><subfield code="c">electronic book</subfield><subfield code="9">1-000-78930-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781003272649</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-003-27264-9</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1003272649</subfield><subfield code="c">electronic book</subfield><subfield code="9">1-003-27264-9</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1000789500</subfield><subfield code="c">electronic book</subfield><subfield code="9">1-000-78950-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781000789508</subfield><subfield code="c">electronic book</subfield><subfield code="9">978-1-000-78950-8</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)102560358</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP102560358</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781000789508</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)102560358</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">BUS</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">UB</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.35</subfield><subfield code="2">23</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Graph Learning and Network Science for Natural Language Processing</subfield><subfield code="c">edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boca Raton, FL</subfield><subfield code="b">CRC Press</subfield><subfield code="c">2023</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Computational intelligence techniques</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on online resource; title from digital title page (viewed on February 08, 2023)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Natural language processing (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Graph theory</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">System analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Traitement automatique des langues naturelles</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Analyse de systèmes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">systems analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">BUSINESS & ECONOMICS / Statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COMPUTERS / Database Management / Data Mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COMPUTERS / Machine Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Graph theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Natural language processing (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">System analysis</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Garg, Muskan</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gupta, Amit Kumar</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Prasad, Rajesh</subfield><subfield code="e">HerausgeberIn</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="1" ind2=" "><subfield code="z">9781000789508</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781000789508</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781000789508/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-102560358 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:15Z |
| institution | BVB |
| isbn | 9781000789300 1000789306 9781003272649 1003272649 1000789500 9781000789508 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource. |
| psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | CRC Press |
| record_format | marc |
| series2 | Computational intelligence techniques |
| spelling | Graph Learning and Network Science for Natural Language Processing edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad Boca Raton, FL CRC Press 2023 ©2023 1 Online-Ressource. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational intelligence techniques Description based on online resource; title from digital title page (viewed on February 08, 2023) Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning. Natural language processing (Computer science) Graph theory System analysis Traitement automatique des langues naturelles Analyse de systèmes systems analysis BUSINESS & ECONOMICS / Statistics COMPUTERS / Database Management / Data Mining COMPUTERS / Machine Theory Garg, Muskan HerausgeberIn edt Gupta, Amit Kumar HerausgeberIn edt Prasad, Rajesh HerausgeberIn edt 9781000789508 Erscheint auch als Druck-Ausgabe 9781000789508 |
| spellingShingle | Graph Learning and Network Science for Natural Language Processing Natural language processing (Computer science) Graph theory System analysis Traitement automatique des langues naturelles Analyse de systèmes systems analysis BUSINESS & ECONOMICS / Statistics COMPUTERS / Database Management / Data Mining COMPUTERS / Machine Theory |
| title | Graph Learning and Network Science for Natural Language Processing |
| title_auth | Graph Learning and Network Science for Natural Language Processing |
| title_exact_search | Graph Learning and Network Science for Natural Language Processing |
| title_full | Graph Learning and Network Science for Natural Language Processing edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad |
| title_fullStr | Graph Learning and Network Science for Natural Language Processing edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad |
| title_full_unstemmed | Graph Learning and Network Science for Natural Language Processing edited by Muskan Garg, Amit Kumar Gupta, Rajesh Prasad |
| title_short | Graph Learning and Network Science for Natural Language Processing |
| title_sort | graph learning and network science for natural language processing |
| topic | Natural language processing (Computer science) Graph theory System analysis Traitement automatique des langues naturelles Analyse de systèmes systems analysis BUSINESS & ECONOMICS / Statistics COMPUTERS / Database Management / Data Mining COMPUTERS / Machine Theory |
| topic_facet | Natural language processing (Computer science) Graph theory System analysis Traitement automatique des langues naturelles Analyse de systèmes systems analysis BUSINESS & ECONOMICS / Statistics COMPUTERS / Database Management / Data Mining COMPUTERS / Machine Theory |
| work_keys_str_mv | AT gargmuskan graphlearningandnetworksciencefornaturallanguageprocessing AT guptaamitkumar graphlearningandnetworksciencefornaturallanguageprocessing AT prasadrajesh graphlearningandnetworksciencefornaturallanguageprocessing |