Practical Text Analytics - Maximizing the Value of Text Data (Paperback, Softcover reprint of the original 1st ed. 2019)

This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Advances in Analytics and Data Science, 2
Release date:	December 2018
First published:	2019
Authors:	Murugan Anandarajan • Chelsey Hill • Thomas Nolan
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Paperback
Pages:	285
Edition:	Softcover reprint of the original 1st ed. 2019
ISBN-13:	978-3-03-007080-9
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Business & management > Business mathematics & systems > General
LSN:	3-03-007080-8
Barcode:	9783030070809

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