SAS® Visual Text Analytics in SAS® Viya®

Text analysts, business and marketing analysts, web analysts, BI professionals, customer intelligence professionals, social media analysts, and document librarians

• Use the point-and-click interface of Model Studio and SAS Visual Text Analytics.
• Explore collections of text documents to discover key topics.
• Interpret term maps.
• 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.
• Extract individual instances of concepts from within documents.
• Create custom Boolean rules to categorize documents with respect to a categorical target variable.
• Modify automatically generated Boolean category rules.
• Extract a document-level sentiment score.
• Create modeling-ready data for use by SAS Visual Data Mining and Machine Learning.

Neither SAS programming experience nor statistical knowledge is required. You should be comfortable using a computer, have experience using browser-based software solutions, and have a basic understanding of the differences between structured (numeric) and unstructured (text) data fields.

Introduction to SAS Visual Text Analytics

• Introduction
• Language challenges (self-study)

SAS Visual Text Analytics Demonstrations

• Importing document collections
• Creating a project with no predefined concepts
• A project with custom concepts

SAS Visual Text Analytics Nodes

• Introduction
• Concepts and terms
• Machine-generated topics
• Categories
• Scoring new documents

Concept and Category Rule Definitions

• SAS Visual Text Analytics rules
• SAS Visual Text Analytics concept rules
• SAS Visual Text Analytics demo category rules

Case Studies

• Retrieving information and documents about anxiety and depression from drug reports
• Automatic categorization of ASRS incident reports
• Retrieving mortgage complaints from the CFPB customer complaints data (self-study)