The Semantic Web Stack.

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Breakthrough Analysis: Two + Nine Types of Semantic Search > > Intelligent Enterprise: Better Insight for Business Decisions.

Semantics is hot, but only in a geeky sort of way. Contrast with search, which long ago shed its geeky image to become the Web’s #1 utility. Search and semantics have similar goals and rely on similar technologies. Both apply data-structuring techniques to make information more findable and usable. Join the two and you get semantic search, in essence, search made smarter, search that seeks to boost accuracy by taming ambiguity via an understanding of context.

Semantic search is still in a definitional phase, “on its way!” as claimant Hakia puts it. Yet Hakia’s own site, still in beta, only confuses with its challenge to “Compare with Google.” I compared, using a term Hakia suggested, carrots. Results look pretty similar, no? So what, exactly, are the ingredients of semantic search?

Semantics (in an IT setting) is meaningful computing: the application of natural language processing (NLP) to support information retrieval, analytics, and data-integration that compass both numerical and “unstructured” information. The ever-emerging Semantic Web is, for many, the poster child, although semantic computing is advancing rapidly even while a portion of the folks who push semantic technologies seem unable to explain clearly and convincingly what business value they deliver.

Continues @http://intelligent-enterprise.informationweek.com

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