Practical text analytics : interpreting text and unstructured data for business intelligence / Steven Struhl.

Format:

Book

Author/Creator:

Struhl, Steven M., author.

Series:

Marketing Science

Marketing Science Series

Language:

English

Subjects (All):

Marketing--Data processing.

Marketing.

Big data.

Business intelligence.

Marketing research.

Physical Description:

1 online resource (272 p.)

Place of Publication:

London, England ; Philadelphia, Pennsylvania ; New Delhi, India : Kogan Page, 2015.

Language Note:

English

System Details:

Mode of access: World Wide Web.

Summary:

Bridging the gap between the marketer who must put text analytics to use and the increasingly rarefied community of data analysis experts, Practical Text Analytics is an accessible guide to the many remarkable advances in text analytics that specialists are discussing among themselves. Instead of being a resource for programmers, a book on theory or an introduction on how to use advanced statistical programs, this daily reference resource cuts through the profusion of jargon, evaluating the strengths and weaknesses of various methods and serving as a guide to what is credible in this fast-movi

Contents:

Machine generated contents note: Preface01 Who should read this book?

Who should read this book

Where we find text

Sense and sensibility in thinking about text

A few places we will not be going

Where we will be going from here

Summary

References02 Getting ready: capturing, sorting, sifting, stemming and matching

What we need to do with text

Ways of corralling words

References03 In pictures: word clouds, wordles and beyond

Getting words into a picture

The many types of pictures and their uses

Clustering words

Applications, uses and cautions

References04 Putting text together: clustering documents using words

Where we have been and moving on to documents

Clustering and classifying documents

Clustering documents

Document classification

References05 In the mood for sentiment (and counting)

Basics of sentiment and counting

Counting words

Understanding sentiment

References06 Predictive models 1: having words with regressions

Understanding predictive models

Starting from the basics with regression

Rules of the road for regression

Divergent roads: regression aims and regression uses

Practical examples

References07 Predictive models 2: classifications that grow on trees

Classification trees: understanding an amazing analytical method

Seeing how trees work, step by step

CHAID and CART (and CRT, C&RT, QUEST, J48 and others)

Summary: applications and cautions

References08 Predictive models 3: all in the family with Bayes Nets

What are Bayes Nets and how do they compare with other methods?

Our first example: Bayes Nets linking survey questions and behaviour

Using a Bayes Net with text

Bayes Net software: welcome to the thicket

Summary, conclusions and cautions

References09 Looking forward and back

Where we may be going

What role does text analytics play?

Summing up: where we have been

Software and you

In conclusion

References Glossary

Index .

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

Other Format:

Print version: Struhl, Steven M. Practical text analytics : interpreting text and unstructured data for business intelligence.

ISBN:

9780749474027

0749474025

9780749474010

0749474017

OCLC:

913562930