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Exploring Textual Data (Hardcover, 1998 ed.): Ludovic Lebart, A. Salem, L Berry Exploring Textual Data (Hardcover, 1998 ed.)
Ludovic Lebart, A. Salem, L Berry
R4,377 Discovery Miles 43 770 Ships in 10 - 15 working days

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.

Exploring Textual Data (Paperback, Softcover reprint of the original 1st ed. 1998): Ludovic Lebart, A. Salem, L Berry Exploring Textual Data (Paperback, Softcover reprint of the original 1st ed. 1998)
Ludovic Lebart, A. Salem, L Berry
R4,276 Discovery Miles 42 760 Ships in 10 - 15 working days

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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