SAS Enterprise Content Categorization applies natural language processing (NLP) and advanced linguistic techniques to identify key topics and phrases in electronic text – automatically categorizing large volumes of multilingual content that is acquired, generated or exists in a repository.
It drives faster, more efficient information insight, organization and delivery by reducing manual tagging and indexing efforts. It also improves collaborative knowledge development, retention and sharing.
Find the information you need, when you need it.
Find the information you need regardless of whether it's been used before or whether you know its exact location.
The flexible, intuitive software provides multiple ways to improve content retrieval, as it accurately defines metadata from the content itself and delivers only the most meaningful material related to your needs.
Improve efficiency and purge content chaos.
In the era of inexpensive commodity storage, it isn't efficient or effective for organizations to retain all of their data.
By categorizing and extracting texts based on sophisticated linguistic rules and taxonomies, you keep only what is needed – and you can filter the information even before it has been stored, to reduce overhead.
Extend existing investments.
The software transforms corporate textual data into a reusable asset, extending the value of predefined investments by building upon existing indexes and integrating with content management systems like Documentum and Microsoft SharePoint, and with search technologies like Endeca and FAST ESP.
- Entity and fact extraction
- Collaborative taxonomy management
- Add-on industry taxonomy starter kits