Smart content just keeps getting better
Smart content continues to learn about you from your usage patterns, using adaptive knowledge management technology to generate and maintain document knowledge signatures. It uses document knowledge signatures to dynamically build user and group knowledge, interest, and collaborative profiles as their cognitive maps. And, it uses document signatures in smart portal applications to direct document distribution, routing, content reduction, and organization around users and workgroups based on their cognitive profiles on a timely basis to facilitate the learning process.

Smart portals with smart content personalization
Workspace portals today provide a personalization service that permits users, groups, and corporations to customize document and portal font, color, and layout--the "look and feel." Smart content can take portal personalization to the next level of corporate productivity by adding automatic content focusing.

Automatic content focusing can personalize information content beyond look and feel by focusing content on what you know and how you learn. With smart portals, information that's most relevant to your specific business needs is brought to you in a way that's optimized to your way of thinking and learning for quick assimilation, decisive decision making, and powerful decision support.

Mapping content to context
Automatic content focusing brings content that matters to you to the surface by semantically parsing documents into content components that are tagged with XML by their knowledge class and mapped to the document's knowledge signature. The document signature is a document knowledge tree that represents its table of context. Each node in the tree is a key phrase representing document context structure to which document content components (e.g, paragraphs) are mapped.

Smart SQL extends smart content
In addition to mapping document components to document signatures, smart content can also automatically generate SQL (Structured Query Language) searches to find and retrieve relevant information in corporate databanks. It can also automatically organize query results around the context of the problem at hand and respective user profiles. Through this method, natural language, whether spoken in voice clips or written in document snippets, can be used as smart content to generate representative SQL to monitor, retrieve, and organize corporate database information for quicker and deeper learning. This facilitates fast, decisive decisions with powerful decision support.

As such, content becomes an instance of context. That is, for each node phrase, a number of document paragraphs would be mapped to each phrase node in the knowledge signature as representative text defining the meaning or semantics of the node. Users can view a document through its document signature and explore the meaning at each node by viewing representative paragraphs accordingly.

In this manner, a user only need read the document signature to get a map of what a document is about. They need only explore some of the nodes and some of the node content (paragraphs) in a directed learning fashion to quickly and deeply understand document content at a sufficiently detailed level to move on to the next level of decision making. These directed reading and learning methods are key techniques used in speed-reading and power-reading for quickly assimilating large volumes of information. In effect, by using such a system, you can learn by example such skills as speed-reading (to raise their reading speed to 800-1500 words per minute) and power-reading (to raise their reading level to thousands of words per minute).