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jargonaut said…
The current query technology limits user’s allowable contextual input. The rule: garbage-in-garbage-out still holds. Vocabulary-oriented Ontology-based “Fuzzy AI” enables very articulate user input of the contextual nuances of entire ideas.

“AI does not mean “self aware”. Real AI would allow an out come of a problem to be produced from known data and from the ability to fill in the blanks of data unknown. Real AI adds a “maybe”. John Pusinsky calls this "grey logic." We are already close, MIT Press publishes: Ontologies for Bioinformatics - the last chapter outlines Ken Baclawski's path to John's – “maybe” - "The Bayesian Web." An implemented "fuzzy AI" example of “semantically intelligent vocabulary filtering” is located at Boston Children’s Hospital’s “Center on Media and Child Health.” www.cmch.tv/research/. Scalable Ontology-Based NLP eliminates the need for “query structuring” by a user. O-BNLP excels with unrestricted length conversational style queries - lots of “context.” At CMCH, pre-indexed “abstractions” of content from ten different “social science” professions are filtered by the underlying SKIP technology and ordered more precisely when the seeker is using “jargon”, well-articulated community-unique vocabulary. Try some questions like: What is the impact of the media on adolescent sexual attitudes and behaviors? Or, Can parents prevent children from experiencing unwanted effects of violent television?
September 15, 2007 at 7:35:00 AM EST
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