Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and cluster analysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.
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`... this book should becomne an essential reference for any researcher interested in the quantitative analysis of textual data. I know of no other book that covers the same range of topics with this amount of detail. ... researchers from any field who use quantitative techniques to process texts should find much here that will be of use.'
Computational Linguistics, 25:1 (1999)
Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and cluster analysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Hardcover. Condición: Bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Couverture différente. Edition 1997. Tome 4. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slight signs of wear on the cover. Different cover. Edition 1997. Volume 4. Ammareal gives back up to 15% of this item's net price to charity organizations. Nº de ref. del artículo: D-597-745
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Hardcover. Condición: new. Hardcover. Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts. This volume demonstrates how exploratory multivariate statistical methods such as correspondence analysis and cluster analysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780792348405
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts. Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and cluster analysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided. 264 pp. Englisch. Nº de ref. del artículo: 9780792348405
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data. Nº de ref. del artículo: 5968290
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