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Building Taxonomies and Ontologies has Value - It Will Transform Content Management
"Gartner Group estimates, that by 2005, 15 percent of user's content management budget will be devoted to taxonomy creation and meta-tagging tools."

Jarg Search Solution
Problem Solution
Retrieve "Whole Ideas" Apply Natural Language Processing
Language Complexity Employ a Semantic solution which understands concepts and relationships (ontology)
Poor Communication between Fields Handle multiple ontologies
Large Volume of Material Fast Retrieval of "Whole Ideas"
Cope with Growth of Knowledge Feed back core knowledge into SKIP's ontology

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Applications

Jarg's products bring new power to these kinds of applications...

Enterprise Search

Professionals in organizations need more subtle ways of finding the information they need. The current generation of consumer search engines do not yet define the "last word" in search.

Semantic representations of what can be found, combined with thoughtful natural language queries, offer new possibilities for discovering knowledge expressed as "whole ideas".

Because the ontology can be maintained to be up-to-date with change in the business, SKIP always represents the latest of "what is known".

The ontology also forms a link between unstructured and structured information, so that SKIP forms a window into all aspects of enterprise knowledge in side the firewall and beyond.

 

Categorization

Categorization by manual intervention is wasteful and idiosyncratic. Automatic knowledge extraction is faster and more uniform. Apply your best information scientists to maintaining the ontology, not reviewing individual articles.

SKIP™ can be applied as a platform for processing articles on a real time basis.

 

Integration of Information across the Enterprise

When information exists in diverse places across the enterprise, the most signifcant cost is to share it effectively. The challenge goes far beyond the technology for making the network connection. Professionals need to draw on many sources, and simple inconsistencies of meaning will bar the door to complete access.

Manual inspection and linking by database administrators is no longer effective. A semantic integration layer is needed over the data warehouse and network middleware, to interpret queries into the form in which an idea is stored.