Overview
- A unique contribution to the analysis of big textual data
- The first book that presents the overarching notion of text mining, ranging from lexical acquisition to NLP applications
- The book strikes a balance between the overall vision and the general picture and current topics in text mining research
- Includes supplementary material: sn.pub/extras
Part of the book series: Theory and Applications of Natural Language Processing (NLP)
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Table of contents (11 chapters)
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Front Matter
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Text Mining Techniques and Methodologies
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Front Matter
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Text Mining Applications
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Front Matter
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Keywords
About this book
This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects the most recent achievements with respect to the automatic build-up of large lexical resources. It addresses researchers that already perform text mining, and those who want to enrich their battery of methods. Selected articles can be used to support graduate-level teaching.
The book is suitable for all readers that completed undergraduate studies of computational linguistics, quantitativelinguistics, computer science and computational humanities. It assumes basic knowledge of computer science and corpus processing as well as of statistics.
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Text Mining
Book Subtitle: From Ontology Learning to Automated Text Processing Applications
Editors: Chris Biemann, Alexander Mehler
Series Title: Theory and Applications of Natural Language Processing
DOI: https://doi.org/10.1007/978-3-319-12655-5
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-12654-8Published: 14 January 2015
Softcover ISBN: 978-3-319-35930-4Published: 24 September 2016
eBook ISBN: 978-3-319-12655-5Published: 19 December 2014
Series ISSN: 2192-032X
Series E-ISSN: 2192-0338
Edition Number: 1
Number of Pages: X, 238
Number of Illustrations: 27 b/w illustrations, 23 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Information Storage and Retrieval, Information Systems Applications (incl. Internet), Computer Appl. in Arts and Humanities, Computer Appl. in Administrative Data Processing