SAS® Text Analytics
Maximize the value buried in unstructured data assets
SAS helps you incorporate these insights to create new metadata for search and document retrieval relevancy and to improve predictive accuracy, provide greater understanding to organizational reports and streamline business priorities – driving proactive, evidence-based business decisions.
Components of SAS® Text Analytics
- SAS Enterprise Content Categorization – Drive faster, more relevant information organization, search and retrieval with automated content categorization. Add-on modules offer prebuilt taxonomies, Web crawling, search and indexing, duplication document identification, text summarization and more.
- SAS Ontology Management – Maximize value across your text repositories by linking them together consistently and systematically using semantic relationships.
- SAS Sentiment Analysis – Automatically locate and analyze the sentiment of electronic text in real time from websites, internal files and reports, surveys, forms, emails and communication centers to spot trends and identify customer priorities.
- SAS Text Miner – Discover topics and patterns within entire document collections by mining unstructured data sources.
How SAS® Is Different
- SAS provides a rich suite of tools for discovering and extracting knowledge from text documents, including a comprehensive text mining solution that integrates text-based information with structured data and predictive analytics for better answers to complex questions.
- SAS uses a combination of advanced statistical modeling, natural language processing and advanced linguistic technologies to quickly and automatically examine large volumes of multilingual content to discover trends, patterns and sentiments locked away in textual content.
- SAS enables you to take full advantage of content assets and ensure reuse across disparate departmental repositories, regardless of who owns the content or where it was generated.
- SAS helps you better manage the customer experience, mine multiple sources to find important patterns, create early-warning systems related to key processes, and enhance research efforts, product development and messaging.





