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Sinopsis
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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Acerca del autor
After completing his doctoral dissertation with Gerhard Heyer at the University of Leipzig (Germany), Chris Biemann joined the semantic search startup Powerset (San Francisco) in 2008, which was acquired to become part of Microsoft's Bing in the same year. In 2011, he joined TU Darmstadt (Germany) as an assistant professor (W1) for Language Technology. His interests are situated in statistical semantics, unsupervised and knowledge-free natural language processing and in leveraging the wisdom of the crowds for language data acquisition. Alexander Mehler is professor (W3) for Computational Humanities / Text Technology at the Goethe University Frankfurt am Main, where he heads the Text Technology Lab as part of the Institute of Informatics. His research interests focus on the empirical analysis and simulative synthesis of discourse units in spoken and written communication. He aims at a quantitative theory of networking in linguistic systems to enable multi-agent simulations of their lifecycle. Alexander Mehler integrates models of semantic spaces with simulation models of language evolution and topological models of network theory to capture the complexity of linguistic information systems. Currently, he is heading several research projects on the analysis of linguistic networks in historical semantics. Most recently he started a research project on kinetic text-technologies that integrates the paradigm of games with a purpose with the wiki way of collaborative writing and kinetic HCI.
De la contraportada
?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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Text Mining. From Ontology Learning to Automated Text Processing Applications.
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Cham, Springer., 2014
ISBN 10: 3319126547
ISBN 13: 9783319126548
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x, 238 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Nº de ref. del artículo: 3430CB
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Text Mining : From Ontology Learning to Automated Text Processing Applications
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Springer International Publishing, 2015
ISBN 10: 3319126547
ISBN 13: 9783319126548
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Text Mining
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Springer International Publishing, 2015
ISBN 10: 3319126547
ISBN 13: 9783319126548
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Text Mining: From Ontology Learning to Automated Text Processing Applications (Theory and Applications of Natural Language Processing)
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Text Mining
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Springer International Publishing Jan 2015, 2015
ISBN 10: 3319126547
ISBN 13: 9783319126548
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 248 pp. Englisch. Nº de ref. del artículo: 9783319126548
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Text Mining : From Ontology Learning to Automated Text Processing Applications
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Springer International Publishing, 2015
ISBN 10: 3319126547
ISBN 13: 9783319126548
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783319126548
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Text Mining: From Ontology Learning to Automated Text Processing Applications (Theory and Applications of Natural Language Processing)
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Buch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 248 pp. Englisch. Nº de ref. del artículo: 9783319126548
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Text Mining: From Ontology Learning to Automated Text Processing Applications (Theory and Applications of Natural Language Processing)
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