Ebook: Modeling, Learning, and Processing of Text Technological Data Structures
- Tags: Appl.Mathematics/Computational Methods of Engineering, Language Translation and Linguistics, Artificial Intelligence (incl. Robotics), Computational Linguistics
- Series: Studies in Computational Intelligence 370
- Year: 2012
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
Content:
Front Matter....Pages -
Introduction: Modeling, Learning and Processing of Text-Technological Data Structures....Pages 1-11
Front Matter....Pages 13-13
The MOTS Workbench....Pages 15-34
Processing Text-Technological Resources in Discourse Parsing....Pages 35-58
Front Matter....Pages 59-59
Semantic Distance Measures with Distributional Profiles of Coarse-Grained Concepts....Pages 61-79
Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools....Pages 81-93
Front Matter....Pages 95-95
An Introduction to Hybrid Semantics: The Role of Cognition in Semantic Resources....Pages 97-109
Modal Logic Foundations of Markup Structures in Annotation Systems....Pages 111-127
Adaptation of Ontological Knowledge from Structured Textual Data....Pages 129-153
Front Matter....Pages 155-155
Ten Problems in the Interpretation of XML Documents....Pages 157-174
Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration....Pages 175-195
Integrated Linguistic Annotation Models and Their Application in the Domain of Antecedent Detection....Pages 197-218
Front Matter....Pages 219-219
Machine Learning for Document Structure Recognition....Pages 221-247
Corpus-Based Structure Mapping of XML Document Corpora: A Reinforcement Learning Based Model....Pages 249-266
Learning Methods for Graph Models of Document Structure....Pages 267-298
Integrating Content and Structure Learning: A Model of Hypertext Zoning and Sounding....Pages 299-329
Front Matter....Pages 331-331
Learning Semantic Relations from Text....Pages 333-346
Modelling and Processing Wordnets in OWL....Pages 347-376
Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgments....Pages 377-396
Back Matter....Pages -
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
Content:
Front Matter....Pages -
Introduction: Modeling, Learning and Processing of Text-Technological Data Structures....Pages 1-11
Front Matter....Pages 13-13
The MOTS Workbench....Pages 15-34
Processing Text-Technological Resources in Discourse Parsing....Pages 35-58
Front Matter....Pages 59-59
Semantic Distance Measures with Distributional Profiles of Coarse-Grained Concepts....Pages 61-79
Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools....Pages 81-93
Front Matter....Pages 95-95
An Introduction to Hybrid Semantics: The Role of Cognition in Semantic Resources....Pages 97-109
Modal Logic Foundations of Markup Structures in Annotation Systems....Pages 111-127
Adaptation of Ontological Knowledge from Structured Textual Data....Pages 129-153
Front Matter....Pages 155-155
Ten Problems in the Interpretation of XML Documents....Pages 157-174
Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration....Pages 175-195
Integrated Linguistic Annotation Models and Their Application in the Domain of Antecedent Detection....Pages 197-218
Front Matter....Pages 219-219
Machine Learning for Document Structure Recognition....Pages 221-247
Corpus-Based Structure Mapping of XML Document Corpora: A Reinforcement Learning Based Model....Pages 249-266
Learning Methods for Graph Models of Document Structure....Pages 267-298
Integrating Content and Structure Learning: A Model of Hypertext Zoning and Sounding....Pages 299-329
Front Matter....Pages 331-331
Learning Semantic Relations from Text....Pages 333-346
Modelling and Processing Wordnets in OWL....Pages 347-376
Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgments....Pages 377-396
Back Matter....Pages -
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