Trends in Parsing Technology [electronic resource] : Dependency Parsing, Domain Adaptation, and Deep Parsing / edited by Harry Bunt, Paola Merlo, Joakim Nivre.
Erişim Adresi
ISBN
9789048193523
Dil Kodu
İngilizce
Yer Numarası
DK/13275
Basım Bildirimi
1st ed. 2010.
Yayın Bilgisi
Dordrecht : Springer Netherlands : Imprint: Springer, 2010.
Fiziksel Niteleme
X, 298 p. online resource.
Dizi
Text, Speech and Language Technology, 2542-9388 ; 43
İçindekiler Notu
Current Trends in Parsing Technology -- Single Malt or Blended? A Study in Multilingual Parser Optimization -- A Latent Variable Model for Generative Dependency Parsing -- Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles -- Dependency Parsing Using Global Features -- Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information -- Strictly Lexicalised Dependency Parsing -- Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length -- Corrective Dependency Parsing -- Inducing Lexicalised PCFGs with Latent Heads -- Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy -- Are Very Large Context-Free Grammars Tractable? -- Efficiency in Unification-Based N-Best Parsing -- HPSG Parsing with a Supertagger -- Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaptation of an HPSG Parser -- Semi-supervised Training of a Statistical Parser from Unlabeled Partially-Bracketed Data.
Özet, vb.
Parsing technology is a central area of research in the automatic processing of human language. It is concerned with the decomposition of complex structures into their constituent parts, in particular with the methods, the tools and the software to parse automatically. Parsers are used in many application areas, such as information extraction from free text or speech, question answering, speech recognition and understanding, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable. This book collects contributions from leading researchers in the area of natural language processing technology, describing their recent work and a range of new techniques and results. The book presents a state-of-the-art overview of current research in parsing tehcnologies with a focus on three important themes in the field today: dependency parsing, domain adaptation, and deep parsing. This book isthe fourth in a line of such collections, and its breadth of coverage should make it suitable both as an overview of the state of the field for graduate students, and as a reference for established researchers in Computational Linguistics, Artificial Intelligence, Computer Science, Language Engineering, Information Science, and Cognitive Science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
Konu
Computational linguistics.
Natural language processing (Computer science).
Computational Linguistics.
Natural Language Processing (NLP).
Natural language processing (Computer science).
Computational Linguistics.
Natural Language Processing (NLP).
Diğer Yazarlar
Kurum Adı
Eseri Alıntıla
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Dijital Kaynak
MARC Görünümü
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505 0 |aCurrent Trends in Parsing Technology -- Single Malt or Blended? A Study in Multilingual Parser Optimization -- A Latent Variable Model for Generative Dependency Parsing -- Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles -- Dependency Parsing Using Global Features -- Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information -- Strictly Lexicalised Dependency Parsing -- Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length -- Corrective Dependency Parsing -- Inducing Lexicalised PCFGs with Latent Heads -- Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy -- Are Very Large Context-Free Grammars Tractable? -- Efficiency in Unification-Based N-Best Parsing -- HPSG Parsing with a Supertagger -- Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaptation of an HPSG Parser -- Semi-supervised Training of a Statistical Parser from Unlabeled Partially-Bracketed Data.
520 |aParsing technology is a central area of research in the automatic processing of human language. It is concerned with the decomposition of complex structures into their constituent parts, in particular with the methods, the tools and the software to parse automatically. Parsers are used in many application areas, such as information extraction from free text or speech, question answering, speech recognition and understanding, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable. This book collects contributions from leading researchers in the area of natural language processing technology, describing their recent work and a range of new techniques and results. The book presents a state-of-the-art overview of current research in parsing tehcnologies with a focus on three important themes in the field today: dependency parsing, domain adaptation, and deep parsing. This book isthe fourth in a line of such collections, and its breadth of coverage should make it suitable both as an overview of the state of the field for graduate students, and as a reference for established researchers in Computational Linguistics, Artificial Intelligence, Computer Science, Language Engineering, Information Science, and Cognitive Science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
650 0|aComputational linguistics.
650 0|aNatural language processing (Computer science).
650 14|aComputational Linguistics.
650 24|aNatural Language Processing (NLP).
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700 1 |aMerlo, Paola.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
700 1 |aNivre, Joakim.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
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041 |aeng
049 |aTürk Tarih Kurumu Kütüphanesi
050 4|aP98-98.5
072 7|aCFX|2bicssc
072 7|aCOM073000|2bisacsh
072 7|aCFX|2thema
082 04|a410.285|223
090 |aDK/13275
245 10|aTrends in Parsing Technology|h[electronic resource] :|bDependency Parsing, Domain Adaptation, and Deep Parsing /|cedited by Harry Bunt, Paola Merlo, Joakim Nivre.
250 |a1st ed. 2010.
264 1|aDordrecht :|bSpringer Netherlands :|bImprint: Springer,|c2010.
300 |aX, 298 p.|bonline resource.
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
347 |atext file|bPDF|2rda
490 1 |aText, Speech and Language Technology,|x2542-9388 ;|v43
505 0 |aCurrent Trends in Parsing Technology -- Single Malt or Blended? A Study in Multilingual Parser Optimization -- A Latent Variable Model for Generative Dependency Parsing -- Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles -- Dependency Parsing Using Global Features -- Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information -- Strictly Lexicalised Dependency Parsing -- Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length -- Corrective Dependency Parsing -- Inducing Lexicalised PCFGs with Latent Heads -- Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy -- Are Very Large Context-Free Grammars Tractable? -- Efficiency in Unification-Based N-Best Parsing -- HPSG Parsing with a Supertagger -- Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaptation of an HPSG Parser -- Semi-supervised Training of a Statistical Parser from Unlabeled Partially-Bracketed Data.
520 |aParsing technology is a central area of research in the automatic processing of human language. It is concerned with the decomposition of complex structures into their constituent parts, in particular with the methods, the tools and the software to parse automatically. Parsers are used in many application areas, such as information extraction from free text or speech, question answering, speech recognition and understanding, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable. This book collects contributions from leading researchers in the area of natural language processing technology, describing their recent work and a range of new techniques and results. The book presents a state-of-the-art overview of current research in parsing tehcnologies with a focus on three important themes in the field today: dependency parsing, domain adaptation, and deep parsing. This book isthe fourth in a line of such collections, and its breadth of coverage should make it suitable both as an overview of the state of the field for graduate students, and as a reference for established researchers in Computational Linguistics, Artificial Intelligence, Computer Science, Language Engineering, Information Science, and Cognitive Science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
650 0|aComputational linguistics.
650 0|aNatural language processing (Computer science).
650 14|aComputational Linguistics.
650 24|aNatural Language Processing (NLP).
700 1 |aBunt, Harry.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
700 1 |aMerlo, Paola.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
700 1 |aNivre, Joakim.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
710 2 |aSpringerLink (Online service)
773 0 |tSpringer Nature eBook
776 08|iPrinted edition:|z9789048193516
776 08|iPrinted edition:|z9789048193530
776 08|iPrinted edition:|z9789400733794
830 0|aText, Speech and Language Technology,|x2542-9388 ;|v43
856 40|uhttps://doi.org/10.1007/978-90-481-9352-3
912 |aZDB-2-SHU
912 |aZDB-2-SXS
950 |aHumanities, Social Sciences and Law (SpringerNature-11648)
950 |aSocial Sciences (R0) (SpringerNature-43726)
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