Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (v16)

Course details

Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (V16) teaches users how to analyze text data using IBM SPSS Modeler Text Analytics. Students will see the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model to perform Churn analysis. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, and exclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to create resource templates and Text Analysis packages to share work with other projects and other users.

Target Audience:

This course is for: Anyone who needs to analyze text data for the purpose of creating predictive models or reports based in part on text data. Users of IBM SPSS Modeler Text Analytics.

Objectives:

Please refer to the Course Overview for description information.

Prerequisites:

You should have

• General computer literacy
• Practical experience with coding text data is not a prerequisite but would be helpful

You should have completed:

• Introduction to IBM SPSS Modeler and Data Mining course or experience with IBM SPSS Modeler

Content:

• Introduction to Text Mining
• An Overview of Text Mining in IBM SPSS Modeler
• Reading Text Data
• Linguistic Analysis and Text Mining
• Creating a Text Mining Concept Model
• Reviewing Types and Concepts in the Interactive Workbench
• Editing Linguistic Resources
• Fine Tuning Resources
• Performing Text Link Analysis
• Clustering Concepts
• Categorization Techniques
• Creating Categories
• Managing Linguistic Resources
• Using Text Mining Models
• Appendix A: The Process of Text Mining