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  1. Grammars for Language and Genes
    Theoretical and Empirical Investigations
    Author: Chiang, David
    Published: 2012
    Publisher:  Springer-Verlag Berlin Heidelberg, Berlin, Heidelberg

    Grammars are gaining importance in natural language processing and computational biology as a means of encoding theories and structuring algorithms. But one serious obstacle to applications of grammars is that formal language theory traditionally... more

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    Grammars are gaining importance in natural language processing and computational biology as a means of encoding theories and structuring algorithms. But one serious obstacle to applications of grammars is that formal language theory traditionally classifies grammars according to their weak generative capacity (what sets of strings they generate) and tends to ignore strong generative capacity (what sets of structural descriptions they generate) even though the latter is more relevant to applications. This book develops and demonstrates a framework for carrying out rigorous comparisons of gramma

     
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 1283449471; 9783642204449; 9781283449472
    Other identifier:
    Series: Theory and Applications of Natural Language Processing
    Subjects: Computer science; Translators (Computer programs); Bioinformatics
    Scope: Online-Ressource, v.: digital
    Notes:

    Includes bibliographical references and index

    Electronic reproduction; Available via World Wide Web

    Grammars for Language and Genes; Foreword; Acknowledgements; Contents; Chapter 1 Introduction; 1.1 The Problem of Strong Generative Capacity; 1.2 Wine, King,Woman, and Truth; 1.3 The Case of Dutch Cross-Serial Dependencies; 1.4 Overview; Theoretical framework; Statistical parsing; Machine translation; Biological sequence analysis; Chapter 2 Foundation; 2.1 Strong Generative Capacity, Relativized; 2.2 Simple Literal Movement Grammars; 2.3 Interpretation Functions; 2.4 Summary; 2.5 Additional Topics; 2.5.1 Tree-Adjoining Grammars; No adjunction: tree substitution grammars

    No wrapping adjunction: tree-insertion grammarsLimited spine adjunction: regular form; Multiple adjunction and sister adjunction; 2.5.2 Multicomponent Grammars; 2.5.3 Parsing; 2.5.4 Cover Grammars; Chapter 3 Statistical Parsing; 3.1 Measuring Statistical Modeling Power; 3.2 Lexicalized Probabilistic CFG; 3.3 A Probabilistic TIG Model; Basic definition; Independence assumptions and smoothing; Parsing; 3.4 Training from Partial Structural Descriptions; 3.4.1 Rule-Based Reconstruction; 3.4.2 Training by Expectation-Maximization; 3.5 Related Work; 3.6 Summary; Chapter 4 Machine Translation

    4.1 Measuring Translation Power4.2 Translation and Bitext Parsing; 4.3 Synchronous CFG; 4.3.1 Applications to Translation; Inversion transduction grammar; Yamada-Knight syntax-based model; Hiero; 4.3.2 Extensions Synchronous TSG; Synchronous tree sequence substitution grammar; Synchronous TIG; 4.4 Synchronous TAG; 4.4.1 Synchronous Regular Form TAG; 4.4.2 Extensions; Bounded nonisomorphisms: TAG.TSG; A more substantial extension: TAG.RF-TAG; 4.5 Summary; Chapter 5 Biological Sequence Analysis: Basics; 5.1 Background; 5.1.1 Sequences; 5.1.2 Structures; 5.2 Measuring Sequence Analysis Power

    5.3 Linked Grammars for Sequence Analysis5.3.1 Squeezing DGC; Alpha-helices; Limited RNA tertiary interactions; 5.3.2 Beyond CFG; Pseudoknots; Beta-sheets; 5.4 Computing Probabilities and Partition Functions; Calculating energies; Counting conformations; Computing partial sums of the partition function; Implementation details; 5.5 Summary; Chapter 6 Biological Sequence Analysis: Intersection; 6.1 Intersecting CFLs and CFLs: a Critique; 6.2 Intersecting CFGs and Finite-State Automata; 6.2.1 Integrating the Zimm-Bragg Model and the HP Model; 6.2.2 Intersecting the Grammars

    6.2.3 Computing the Partition Function6.2.4 Evaluation Against Exact Enumeration; 6.3 Intersection in Nonlinear sLMGs; 6.4 Summary; Chapter 7 Conclusion; Statistical parsing; Machine translation; Biological sequence analysis; Conclusion; References; Index;
  2. Grammars for Language and Genes
    Theoretical and Empirical Investigations
    Author: Chiang, David
    Published: 2012
    Publisher:  Springer Berlin Heidelberg, Berlin, Heidelberg ; Springer International Publishing AG, Cham

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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9783642204449; 3642204449
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    DDC Categories: 400; 570; 004
    Edition: 1st ed. 2012
    Series: Theory and Applications of Natural Language Processing
    Subjects: Formale Grammatik; Generative Kapazität; Syntaktische Analyse; Maschinelle Übersetzung; Natürliche Sprache; Sequenzdaten; Nucleotidsequenz; Aminosäurensequenz; Machine theory; Natural language processing (Computer science); Bioinformatics; Formal Languages and Automata Theory; Natural Language Processing (NLP); Computational and Systems Biology
    Scope: 1 Online-Ressource (XII, 120 Seiten)
  3. Grammars for Language and Genes
    Theoretical and Empirical Investigations
    Author: Chiang, David
    Published: 2012
    Publisher:  Springer-Verlag Berlin Heidelberg, Berlin, Heidelberg

    1.Introduction -- 2.Foundation -- 3.Statistical Parsing -- 4.Machine Translation -- 5.Biological Sequence Analysis: Basics -- 6.Biological Sequence Analysis: Intersection -- 7.Conclusion -- References -- Index Grammars are gaining importance in... more

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    1.Introduction -- 2.Foundation -- 3.Statistical Parsing -- 4.Machine Translation -- 5.Biological Sequence Analysis: Basics -- 6.Biological Sequence Analysis: Intersection -- 7.Conclusion -- References -- Index Grammars are gaining importance in natural language processing and computational biology as a means of encoding theories and structuring algorithms. But one serious obstacle to applications of grammars is that formal language theory traditionally classifies grammars according to their weak generative capacity (what sets of strings they generate) and tends to ignore strong generative capacity (what sets of structural descriptions they generate) even though the latter is more relevant to applications. This book develops and demonstrates a framework for carrying out rigorous comparisons of grammar formalisms in terms of their usefulness for applications, focusing on three areas of application: statistical parsing, natural language translation, and biological sequence analysis. These results should pave the way for theoretical research to pursue results that are more directed towards applications, and for practical research to explore the use of advanced grammar formalisms more easily

     
    Export to reference management software   RIS file
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    Content information
    Volltext (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9783642204449; 1283449471; 9781283449472
    Other identifier:
    Series: Theory and Applications of Natural Language Processing
    Array
    Subjects: Computer Science; Computer science; Translators (Computer programs); Bioinformatics; Computer science; Translators (Computer programs); Bioinformatics
    Scope: Online-Ressource (XII, 120p. 67 illus, digital)
    Notes:

    Includes bibliographical references and index

    Grammars for Language and Genes; Foreword; Acknowledgements; Contents; Chapter 1 Introduction; 1.1 The Problem of Strong Generative Capacity; 1.2 Wine, King,Woman, and Truth; 1.3 The Case of Dutch Cross-Serial Dependencies; 1.4 Overview; Theoretical framework; Statistical parsing; Machine translation; Biological sequence analysis; Chapter 2 Foundation; 2.1 Strong Generative Capacity, Relativized; 2.2 Simple Literal Movement Grammars; 2.3 Interpretation Functions; 2.4 Summary; 2.5 Additional Topics; 2.5.1 Tree-Adjoining Grammars; No adjunction: tree substitution grammars

    No wrapping adjunction: tree-insertion grammarsLimited spine adjunction: regular form; Multiple adjunction and sister adjunction; 2.5.2 Multicomponent Grammars; 2.5.3 Parsing; 2.5.4 Cover Grammars; Chapter 3 Statistical Parsing; 3.1 Measuring Statistical Modeling Power; 3.2 Lexicalized Probabilistic CFG; 3.3 A Probabilistic TIG Model; Basic definition; Independence assumptions and smoothing; Parsing; 3.4 Training from Partial Structural Descriptions; 3.4.1 Rule-Based Reconstruction; 3.4.2 Training by Expectation-Maximization; 3.5 Related Work; 3.6 Summary; Chapter 4 Machine Translation

    4.1 Measuring Translation Power4.2 Translation and Bitext Parsing; 4.3 Synchronous CFG; 4.3.1 Applications to Translation; Inversion transduction grammar; Yamada-Knight syntax-based model; Hiero; 4.3.2 Extensions Synchronous TSG; Synchronous tree sequence substitution grammar; Synchronous TIG; 4.4 Synchronous TAG; 4.4.1 Synchronous Regular Form TAG; 4.4.2 Extensions; Bounded nonisomorphisms: TAG.TSG; A more substantial extension: TAG.RF-TAG; 4.5 Summary; Chapter 5 Biological Sequence Analysis: Basics; 5.1 Background; 5.1.1 Sequences; 5.1.2 Structures; 5.2 Measuring Sequence Analysis Power

    5.3 Linked Grammars for Sequence Analysis5.3.1 Squeezing DGC; Alpha-helices; Limited RNA tertiary interactions; 5.3.2 Beyond CFG; Pseudoknots; Beta-sheets; 5.4 Computing Probabilities and Partition Functions; Calculating energies; Counting conformations; Computing partial sums of the partition function; Implementation details; 5.5 Summary; Chapter 6 Biological Sequence Analysis: Intersection; 6.1 Intersecting CFLs and CFLs: a Critique; 6.2 Intersecting CFGs and Finite-State Automata; 6.2.1 Integrating the Zimm-Bragg Model and the HP Model; 6.2.2 Intersecting the Grammars

    6.2.3 Computing the Partition Function6.2.4 Evaluation Against Exact Enumeration; 6.3 Intersection in Nonlinear sLMGs; 6.4 Summary; Chapter 7 Conclusion; Statistical parsing; Machine translation; Biological sequence analysis; Conclusion; References; Index;