Trends in Parsing Technology: Dependency Parsing, Domain Adaptation, and Deep Parsing: Text, Speech and Language Technology, cartea 43
Editat de Harry Bunt, Paola Merlo, Joakim Nivreen Limba Engleză Paperback – 6 dec 2012
Din seria Text, Speech and Language Technology
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Specificații
ISBN-13: 9789400733794
ISBN-10: 9400733798
Pagini: 308
Ilustrații: X, 298 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.44 kg
Ediția:2010
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Text, Speech and Language Technology
Locul publicării:Dordrecht, Netherlands
ISBN-10: 9400733798
Pagini: 308
Ilustrații: X, 298 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.44 kg
Ediția:2010
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Text, Speech and Language Technology
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchDescriere
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 is the fourth in a line of such collections, and its breadth over 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 nautral language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
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 is the fourth in a line of such collections, and its breadth over 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 nautral language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
Cuprins
Current Trends in Parsing Technology, Paola Merlo, Harry Bunt and Joakim NivreSingle Malt or Blended? A Study in Multilingual Parser Optimization, Johan Hall, Jens Nilsson and Joakim NivreA Latent Variable Model for Generative Dependency Parsing, Ivan Titov and James HendersonDependency Parsing and Domain Adaption with Data-Driven LR Models and Parser Ensembles, Kenji Sagae and Jun’ichi TsujiiDependency Parsing Using Global Features, Tetsuji NakagawaDependency Parsing with Second-Order Feature Maps and Annotated Semantic Information, Massimiliano Ciaramita and Guiseppe AttardiStrictly Lexicalised Dependency Parsing, Qin Iris Wang, Dale Schuurmans and Dekang LinFavor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length, Jason Eisner and Noah A. SmithCorrective Dependency Parsing, Keith Hall and Václav NovákInducing Lexicalised PCFGs with Latent Heads, Detlef PrescherSelf-Trained Bilexical Preferences to Improve Disambiguation Accuracy, Gertjan van NoordAre Very Large Context-Free Grammars Tractable? Pierre Boullier and Benoît SagotEfficiency in Unification-Based N-Best Parsing, Yi Zhang, Stephan Oepen and John CarrollHPSG Parsing with a Supertagger, Takashi Ninomiya, Takuya Matsuzaki, Yusuke Miyao, Yoshimasa Tsuruoka and Jun‘ichi TsujiiEvaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaption of an HPSG Parser, Tadayoshi Hara, Yusuke Miyao and Jun’ichi TsujiiSemi-supervised Training of a Statistical Parser from Unlabeled Partially-bracketed Data, Rebecca Watson, Ted Briscoe and John CarrollIndex
Textul de pe ultima copertă
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 is the 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.
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 is the 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.
Caracteristici
Collects contributions from many of today’s leading researchers in the area of natural language processing technology
Describes the contributors’ most recent work and a range of new techniques and results
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
Describes the contributors’ most recent work and a range of new techniques and results
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