Advances in Probabilistic and Other Parsing Technologies [electronic resource] / edited by H. Bunt, Anton Nijholt.
Erişim Adresi
ISBN
9789401594707
Dil Kodu
İngilizce
Yer Numarası
DK/16227
Basım Bildirimi
1st ed. 2000.
Yayın Bilgisi
Dordrecht : Springer Netherlands : Imprint: Springer, 2000.
Fiziksel Niteleme
XV, 267 p. online resource.
Dizi
Text, Speech and Language Technology, 2542-9388 ; 16
İçindekiler Notu
1 New Parsing Technologies -- 2 Encoding Frequency Information in Lexicalized Grammars -- 3 Bilexical Grammars and Their Cubic-Time Parsing Algorithms -- 4 Probabilistic Feature Grammars -- 5 Probabilistic GLR Parsing -- 6 Probabilistic Parsing Using Left Corner Language Models -- 7 A New Parsing Method Using A Global Association Table -- 8 Towards a Reduced Commitment, D-Theory Style TAG Parser -- 9 Probabilistic Parse Selection Based on Semantic Co-occurrences -- 10 Let’s Parsetalk — Message-Passing Protocols for Object-Oriented Parsing -- 11 Performance Evaluation of Supertagging for Partial Parsing -- 12 Regular Approximation of CFLs: A Grammatical View -- 13 Parsing By Successive Approximation.
Özet, vb.
Parsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students.
Konu
Computational linguistics.
Artificial intelligence.
User interfaces (Computer systems).
Human-computer interaction.
Natural language processing (Computer science).
Grammar, Comparative and general __ Syntax.
Computational Linguistics.
Artificial Intelligence.
User Interfaces and Human Computer Interaction.
Natural Language Processing (NLP).
Syntax.
Artificial intelligence.
User interfaces (Computer systems).
Human-computer interaction.
Natural language processing (Computer science).
Grammar, Comparative and general __ Syntax.
Computational Linguistics.
Artificial Intelligence.
User Interfaces and Human Computer Interaction.
Natural Language Processing (NLP).
Syntax.
Diğer Yazarlar
Kurum Adı
Eseri Alıntıla
Referansları kullanmadan önce gözden geçirmeniz ve varsa gerekli düzeltmeleri yapmanız önerilir.
Dijital Kaynak
MARC Görünümü
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505 0 |a1 New Parsing Technologies -- 2 Encoding Frequency Information in Lexicalized Grammars -- 3 Bilexical Grammars and Their Cubic-Time Parsing Algorithms -- 4 Probabilistic Feature Grammars -- 5 Probabilistic GLR Parsing -- 6 Probabilistic Parsing Using Left Corner Language Models -- 7 A New Parsing Method Using A Global Association Table -- 8 Towards a Reduced Commitment, D-Theory Style TAG Parser -- 9 Probabilistic Parse Selection Based on Semantic Co-occurrences -- 10 Let’s Parsetalk — Message-Passing Protocols for Object-Oriented Parsing -- 11 Performance Evaluation of Supertagging for Partial Parsing -- 12 Regular Approximation of CFLs: A Grammatical View -- 13 Parsing By Successive Approximation.
520 |aParsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students.
532 8 |aAccessibility summary: This PDF is not accessible. It is based on scanned pages and does not support features such as screen reader compatibility or described non-text content (images, graphs etc). However, it likely supports searchable and selectable text based on OCR (Optical Character Recognition). Users with accessibility needs may not be able to use this content effectively. Please contact us at accessibilitysupport@springernature.com if you require assistance or an alternative format.
532 8 |aInaccessible, or known limited accessibility
532 8 |aNo reading system accessibility options actively disabled
532 8 |aPublisher contact for further accessibility information: accessibilitysupport@springernature.com
650 0|aComputational linguistics.
650 0|aArtificial intelligence.
650 0|aUser interfaces (Computer systems).
650 0|aHuman-computer interaction.
650 0|aNatural language processing (Computer science).
650 0|aGrammar, Comparative and general|xSyntax.
650 14|aComputational Linguistics.
650 24|aArtificial Intelligence.
650 24|aUser Interfaces and Human Computer Interaction.
650 24|aNatural Language Processing (NLP).
650 24|aSyntax.
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020 |a9789401594707|9978-94-015-9470-7
024 7 |a10.1007/978-94-015-9470-7|2doi
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/16227
245 10|aAdvances in Probabilistic and Other Parsing Technologies|h[electronic resource] /|cedited by H. Bunt, Anton Nijholt.
250 |a1st ed. 2000.
264 1|aDordrecht :|bSpringer Netherlands :|bImprint: Springer,|c2000.
300 |aXV, 267 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 ;|v16
505 0 |a1 New Parsing Technologies -- 2 Encoding Frequency Information in Lexicalized Grammars -- 3 Bilexical Grammars and Their Cubic-Time Parsing Algorithms -- 4 Probabilistic Feature Grammars -- 5 Probabilistic GLR Parsing -- 6 Probabilistic Parsing Using Left Corner Language Models -- 7 A New Parsing Method Using A Global Association Table -- 8 Towards a Reduced Commitment, D-Theory Style TAG Parser -- 9 Probabilistic Parse Selection Based on Semantic Co-occurrences -- 10 Let’s Parsetalk — Message-Passing Protocols for Object-Oriented Parsing -- 11 Performance Evaluation of Supertagging for Partial Parsing -- 12 Regular Approximation of CFLs: A Grammatical View -- 13 Parsing By Successive Approximation.
520 |aParsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students.
532 8 |aAccessibility summary: This PDF is not accessible. It is based on scanned pages and does not support features such as screen reader compatibility or described non-text content (images, graphs etc). However, it likely supports searchable and selectable text based on OCR (Optical Character Recognition). Users with accessibility needs may not be able to use this content effectively. Please contact us at accessibilitysupport@springernature.com if you require assistance or an alternative format.
532 8 |aInaccessible, or known limited accessibility
532 8 |aNo reading system accessibility options actively disabled
532 8 |aPublisher contact for further accessibility information: accessibilitysupport@springernature.com
650 0|aComputational linguistics.
650 0|aArtificial intelligence.
650 0|aUser interfaces (Computer systems).
650 0|aHuman-computer interaction.
650 0|aNatural language processing (Computer science).
650 0|aGrammar, Comparative and general|xSyntax.
650 14|aComputational Linguistics.
650 24|aArtificial Intelligence.
650 24|aUser Interfaces and Human Computer Interaction.
650 24|aNatural Language Processing (NLP).
650 24|aSyntax.
700 1 |aBunt, H.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
700 1 |aNijholt, Anton.|eeditor.|4edt|4http://id.loc.gov/vocabulary/relators/edt
710 2 |aSpringerLink (Online service)
773 0 |tSpringer Nature eBook
776 08|iPrinted edition:|z9780792366164
776 08|iPrinted edition:|z9789048155798
776 08|iPrinted edition:|z9789401594714
830 0|aText, Speech and Language Technology,|x2542-9388 ;|v16
856 40|uhttps://doi.org/10.1007/978-94-015-9470-7
912 |aZDB-2-SHU
912 |aZDB-2-SXS
912 |aZDB-2-BAE
950 |aHumanities, Social Sciences and Law (SpringerNature-11648)
950 |aSocial Sciences (R0) (SpringerNature-43726)
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