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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, quantitative linguistics, computer science and computational humanities. It assumes basic knowledge of computer science and corpus processing as well as of statistics.
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Subjects
Natural language processing (computer science), Data mining, Computer science, Oncology, Information storage and retrieval systems, Information systems, 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 ProcessingEdition | Availability |
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1
Text Mining: From Ontology Learning to Automated Text Processing Applications
Nov 11, 2016, Springer
paperback
3319359304 9783319359304
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2
Text Mining: From Ontology Learning to Automated Text Processing Applications
Dec 20, 2014, Springer
hardcover
3319126547 9783319126548
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3
Text Mining: From Ontology Learning to Automated Text Processing Applications
2014, Springer
in English
3319126555 9783319126555
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