Text Mining for Clementine®

What's New in Text Mining for Clementine 12.0?

Organizations are turning to text mining in increasing numbers to tap into the wealth of feedback found in text—including call center notes, surveys, blogs and Web sites, RSS feeds, e-mails, and other types of documents. As content created by individuals becomes more trusted and more global, corporate and public sector organizations are analyzing it for opinions and sentiments that give them a more complete view of their customers and constituents.

Conduct sentiment analysis in more languages

When you understand what people think and feel in their own words, you can draw more reliable conclusions about their future behavior and use that predictive insight to meet their needs more successfully.

Text Mining for Clementine 12.0 is a significant new release that enables you to analyze opinions and sentiments expressed by your customers or constituents in their preferred language. Now you can conduct out-of-the-box analysis of customer sentiments in English, Dutch, French, German, and Spanish, using a solution based on proven, advanced natural language processing (NLP) techniques.

Multi-lingual sentiment analysis helps you capture the attitudes, thoughts, and behaviors of more customers across more markets and channels than ever before. The result? You’ll be able to build more accurate predictive models that will help maximize customer loyalty, satisfaction, and profitability both locally and globally.

Sentiment analysis will also be a valuable asset for creating an effective and comprehensive Enterprise Feedback Management (EFM) strategy—the process of collecting customer data and using the insights gained to make informed business decisions.

Process textual data more efficiently

Text Mining for Clementine 12.0 also includes new features designed to help you analyze data faster and more efficiently. These enhancements include:

Easily accessible text mining node palette. A new, more user-friendly text mining node palette enables you to access all of the text mining capabilities you need directly from Clementine.
Broader verticalization of linguistic resources. Now you can customize templates and libraries for specific business applications directly from the main Clementine toolbar. Enhanced vertical libraries support more industries and applications, including sentiment analysis, CRM, security and intelligence, competitive intelligence, life sciences (i.e. genomics, mesh), and IT.
Text mining results caching. Save time and computing resources by caching your extraction results during an interactive workbench session for reuse. You can use the saved results to bypass upstream processing and reduce the time it takes to re-extract.

A fully integrated data and text mining workbench

Text Mining for Clementine 12.0 supports SPSS’ ongoing commitment to delivering a fully integrated data mining and text mining workbench. To reflect this, the release’s version number now aligns with Clementine 12.0. Text Mining for Clementine 12.0 also builds on the features delivered in previous releases, which included:

Algorithms to speed up preparation of unstructured data
Enhanced graphics for more effective data understanding
The ability to analyze information like RSS feeds (blogs) and HTML pages in just a few mouseclicks
Improvement of graphical user interfaces for increased productivity
Enhancement of linguistic resources
Seamless deployment of text mining models within any SPSS predictive application

For more information about Text Mining for Clementine, contact a sales representative

Contact SPSS Sales