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Modeling, Learning, and Processing of Text Technological Data Structures

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Cover of 'Modeling, Learning, and Processing of Text Technological Data Structures'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Modeling, Learning and Processing of Text-Technological Data Structures
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    Chapter 2 The MOTS Workbench
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    Chapter 3 Processing Text-Technological Resources in Discourse Parsing
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    Chapter 4 Semantic Distance Measures with Distributional Profiles of Coarse-Grained Concepts
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    Chapter 5 Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools
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    Chapter 6 An Introduction to Hybrid Semantics: The Role of Cognition in Semantic Resources
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    Chapter 7 Modal Logic Foundations of Markup Structures in Annotation Systems
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    Chapter 8 Adaptation of Ontological Knowledge from Structured Textual Data
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    Chapter 9 Ten Problems in the Interpretation of XML Documents
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    Chapter 10 Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration
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    Chapter 11 Integrated Linguistic Annotation Models and Their Application in the Domain of Antecedent Detection
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    Chapter 12 Machine Learning for Document Structure Recognition
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    Chapter 13 Corpus-Based Structure Mapping of XML Document Corpora: A Reinforcement Learning Based Model
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    Chapter 14 Learning Methods for Graph Models of Document Structure
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    Chapter 15 Integrating Content and Structure Learning: A Model of Hypertext Zoning and Sounding
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    Chapter 16 Learning Semantic Relations from Text
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    Chapter 17 Modelling and Processing Wordnets in OWL
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    Chapter 18 Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgments
Attention for Chapter 10: Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration
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Chapter title
Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration
Chapter number 10
Book title
Modeling, Learning, and Processing of Text Technological Data Structures
Published by
Springer, Berlin, Heidelberg, January 2011
DOI 10.1007/978-3-642-22613-7_10
Book ISBNs
978-3-64-222612-0, 978-3-64-222613-7
Authors

Massimo Poesio, Nils Diewald, Maik Stührenberg, Jon Chamberlain, Daniel Jettka, Daniela Goecke, Udo Kruschwitz, Poesio, Massimo, Diewald, N., Stührenberg, M., Chamberlain, Jon, Jettka, D., Goecke, D., Kruschwitz, Udo, Diewald, Nils, Stührenberg, Maik, Jettka, Daniel, Goecke, Daniela

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 50%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 1 25%
Agricultural and Biological Sciences 1 25%
Unknown 2 50%