Improve Results by Adding Text to Data Mining

Text mining enables organizations to explore the "unstructured" information contained in text in much the same way that Dta Mining explores tabular or "structured" data. Through text mining, you can uncover hidden patterns, relationships, and trends in text. As a result, you gain greater insight from articles, reports, surveys, call center notes fields, e-mail, Web chat, and other types of text documents.

In addition, our service implementations enable you to build on your text mining efforts with products that help you incorporate text in predictive data mining models—a solution we call Predictive Text Analytics.

Predictive Text Analytics provides a way for your organization to combine structured and unstructured information in the same models. This enables you to draw more reliable conclusions and take more effective action.

By using Predictive Text Analytics, your organization can:

• Uncover concepts and relationships among concepts in text that would be too costly—or even impossible—to detect with other methods
• Improve the "lift" or accuracy of predictive models and, by doing so, make the models more effective
• Deploy results both to the people who make decisions and to automated systems that make recommendations

Additional Types of Data

An estimated 80 percent of an organization's information is contained in text. It's a rich source of potential insight into your organization and your customers. Predictive Text Analytics helps you achieve that insight.

There are many uses for Predictive Text Analytics, in business, government, and in both private-sector and public-sector research.

Supporting customer relationship management (CRM) is one way companies use Predictive Text Analytics.

Proven technologies deliver results. Our solution combines the natural language processing (NLP) linguistic technologies of our text mining products with the advanced data mining capabilities of our data mining workbench. Our solution uses natural language processing (NLP) linguistic technologies to uncover concepts in text. You can then combine text concepts with other data in predictive models.