Why Cognitive Computing Needs the Semantic Web


James Kobielus of Info World recently wrote, "Cognitive computing can't achieve its potential without a strong semantic-processing substrate that executes across diverse content sources… Nova Spivack references IBM Watson in this regard. The cloud service's DeepQA technology incorporates semantic approaches into its very core, balancing the use of strict and shallow semantics and leveraging many loosely formed ontologies to deliver precise answers to natural-language queries. In my recent big data predictions for 2014, I state that cognitive computing -- much of which will move into the cloud -- incorporates and extends the innovations pioneered by the semantic Web community."


Kobielus continues, "You could view cognition in the cloud, per Spivack's discussion, as the next evolutionary plateau for the semantic Web. But this demands we have a shared understanding of the relationship between the concepts of "cognitive computing" and "semantic computing." The affinity is clear cut. Cognitive computing refers to the ability of automated systems to handle conscious, critical, logical, attentive, reasoning modes of thought. Semantic computing facilitates and automates the cognitive processes involved in defining, modeling, translating, transforming, and querying the deep meanings of words, phrases, and concepts. Semantic computing is what natural-language processing, the heart of cognitive computing, is doing. Data scientists use cognitive-computing tools -- natural-language processing, pattern recognition, and machine learning -- to extract the implicit semantics from unstructured content sources."


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