Learn how text analytics can help your organization gain significant, measurable benefits from textual data.

It's no secret that the world has seen an explosion of information in the past 15 years, an explosion that experts predict will continue as the millions of people who use online resources continue to expand their usage, and the millions of people who do not yet have access to such resources gain it. Similarly, information stored as text in both business and government organizations has grown exponentially.

This paper briefly discusses:

• what text analytics is
• the various approaches to text analytics
• the natural language processing techniques used by SPSS Inc.'s text analytics solutions
• SPSS Inc.'s solutions for text analytics and their role in predictive analytics

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"Mastering New Challenges in Text Analytics: Making unstructured data ready for predictive analytics"

Offered Free by: SPSS, Inc

TABLE OF CONTENTS
Introduction.......................................................................................................................... 2
What is text analytics and how is it used?.............................................................................. 3
Approaches to understanding text......................................................................................... 4
The SPSS text analytics process............................................................................................. 5
Applying text analytics at the enterprise level...................................................................... 17
Conclusion......................................................................................................................... 17
SPSS products for text analytics........................................................................................... 18
About SPSS Inc.................................................................................................................... 18
Appendix A: An explanation of some text analytics terms.................................................... 19
Appendix B: Algorithms used for assigning equivalence classes.......................................... 21
Appendix C: Examples of Text Link Analysis......................................................................... 22
Additional reading on text analytics..................................................................................... 23

INTRODUCTION
It’s no secret that the world has seen an explosion of information in the past 15 years, an explosion that experts predict will continue as the millions of people who use online resources continue to expand their usage, and the millions of people who do not yet have access to such resources gain it. Similarly, information stored as text in both business and government organizations has grown exponentially.

To name just a few examples:

• Opinion surveys are increasingly conducted online and results shared in real time
• The boom in software applications supporting sales, customer service, or call center operations has led to massive amounts of text stored electronically in these applications’ notes fields
• Technology analysts at IDC estimate that 62 billion e-mails are sent every day
• Searchable Web sites generate enough information every day to fill millions of books
• Web logs (blogs) and wikis, created by individuals and groups for personal and professional purposes are increasing

exponentially: as of this writing, there may be more than 100 million blogs, with a new one created every second
Such a vast expansion of the scale of global information exchange would have been almost unimaginable 40 years ago, when most business and government communications, as well as news reports and advertising, were paper-based. ...

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