Cantitate/Preț
Produs

Practical Text Analytics – Interpreting Text and Unstructured Data for Business Intelligence

Autor Steven Struhl
en Limba Engleză Paperback – 2 iul 2015
In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs. Practical Text Analytics is an essential daily reference resource, providing real-world guidance on the effective application of text analytics. The book presents the analysis process so that it is immediately understood by the marketing professionals who must use it, so they can apply proven concepts and methods correctly and with confidence. By decoding industry terminology and demonstrating practical application of data models once reserved for experts, Practical Text Analytics shows marketers how to frame the right questions, identify key themes and find hidden meaning from unstructured data. Readers will learn to develop powerful new marketing strategies to elevate customer experience, solidify brand value and elevate reputation.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 30910 lei  6-8 săpt.
  Kogan Page – 2 iul 2015 30910 lei  6-8 săpt.
Hardback (1) 73148 lei  6-8 săpt.
  Kogan Page – 2 mar 2016 73148 lei  6-8 săpt.

Preț: 30910 lei

Nou

Puncte Express: 464

Preț estimativ în valută:
5916 6153$ 4958£

Carte tipărită la comandă

Livrare economică 13-27 martie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780749474010
ISBN-10: 0749474017
Pagini: 272
Ilustrații: black & white illustrations
Dimensiuni: 156 x 233 x 12 mm
Greutate: 0.36 kg
Editura: Kogan Page

Notă biografică

Steven Struhl

Cuprins

Chapter - 01: Who should read this book? And what do you want to do today?; Chapter - 02: Getting ready: capturing, sorting, sifting, stemming and matching; Chapter - 03: In pictures: word clouds, wordles and beyond; Chapter - 04: Putting text together: clustering documents using words; Chapter - 05: In the mood for sentiment (and counting) ; Chapter - 06: Predictive models 1: having words with regressions; Chapter - 07: Predictive models 2: classifications that grow on trees; Chapter - 08: Predictive models 3: all in the family with Bayes Nets; Chapter - 09: Looking forward and back