Editors:
- Focuses on procedural aspects of automatic text analysis
- Integrates research in the upcoming and challenging text related disciplines. Such as computational linguistics, natural language processing, information retrieval, text and web mining as well as text and language technology
- Integrates a broad range of methods from text-technology, computational linguistics and machine learning
- Special emphasis is put on structure learning. Going beyond classical content-related text representation models in information retrieval and computational linguistics
Part of the book series: Studies in Computational Intelligence (SCI, volume 370)
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Table of contents (18 chapters)
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Front Matter
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Introduction: Modeling, Learning and Processing of Text-Technological Data Structures
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Part I: Text Parsing: Data Structures, Architecture and Evaluation
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Front Matter
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Part II: Measuring Semantic Distance: Methods, Resources, and Applications
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Front Matter
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Part III: From Textual Data to Ontologies, from Ontologies to Textual Data
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Front Matter
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Part IV: Multidimensional Representations: Solutions for Complex Markup
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Front Matter
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Part V: Document Structure Learning
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Front Matter
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About this book
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.
Editors and Affiliations
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Faculty of Linguistics and Literature, Bielefeld University, Bielefeld, Germany
Alexander Mehler
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Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany
Kai-Uwe Kühnberger
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Angewandte Sprachwissenschaft und, Justus-Liebig-Universität Gießen, Gießen, Germany
Henning Lobin, Harald Lüngen
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Institut für deutsche Sprache und Literatur, Technical University Dortmund, Dortmund, Germany
Angelika Storrer
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SFB 441 Linguistic Data Structures, Eberhard Karls Universität Tübingen, Tübingen, Germany
Andreas Witt
Bibliographic Information
Book Title: Modeling, Learning, and Processing of Text-Technological Data Structures
Editors: Alexander Mehler, Kai-Uwe Kühnberger, Henning Lobin, Harald Lüngen, Angelika Storrer, Andreas Witt
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-22613-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-22612-0Published: 10 September 2011
Softcover ISBN: 978-3-642-26944-8Published: 27 November 2013
eBook ISBN: 978-3-642-22613-7Published: 14 October 2011
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 400
Topics: Mathematical and Computational Engineering, Natural Language Processing (NLP), Artificial Intelligence, Computational Linguistics