This course describes the functionality of SAS Contextual Analysis, a single web application that brings together the techniques used in text mining, categorization, contextual extraction, and sentiment identification. SAS Contextual Analysis helps you derive key business insight from unstructured text. It uses a combination of machine learning, linguistic, and subject matter expertise to uncover trends and themes in your data--insights that otherwise would have stayed hidden but can now give you an in-depth understanding of your business.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual Lab time to practice.
- Use the point-and-click GUI interface of SAS Contextual Analysis.
- Explore collections of text documents to discover key topics.
- Interpret term and topic maps and term clouds.
- Identify key textual topics automatically in your large document collections.
- Create robust models for categorizing the content according to your organization’s specific needs.
- Create, modify, and enable (or disable) custom concepts and test linguistic rule definitions with validation checks within the same interactive GUI.
- Modify automatically generated Boolean category rules.
- Import existing SAS Content Categorization taxonomies for project initiation.
- Extract the document-level sentiment score.
Who Can Benefit
- Text analysts, business and marketing analysts, web analysts, BI professionals, customer intelligence professionals, and social media analysts
- Experience in SAS programming or statistical knowledge is not required to attend. You should be able to log on and off a computer, use a keyboard and mouse, and have a preliminary understanding of the differences between structured (numeric) and unstructured (text) data fields.