Semantic computing and cognitive computing/informatics

Semantic Computing (SC) addresses the derivation, description, integration, and use of semantics (“meaning”, “context”, “intention”) for all types of resource including data, document, tool, device, process and people. A broader definition of Semantic Computing includes the computing technologies (e.g., artificial intelligence, natural language, software engineering, data and knowledge engineering, computer systems, signal processing, etc.), and their interactions, that may be used to extract or process computational content. This connection between content and the user is made via Semantic Analysis, which analyzes content with the goal of converting it to machine processable descriptions (semantics); Semantic Integration, which integrates content and semantics from multiple sources; Semantic Applications, which utilize content and descriptions to solve problems; and Semantic Interface, which interprets users' intentions expressed in natural language or other communicative forms. The reverse connection converts the intentions of users to create content via analysis and synthesis techniques. This talk introduces Semantic Computing based on its broader and narrower definitions, its relationship with Artificial Intelligence, Cognitive Computing and Informatics, and other branches of Computer Science. It also discusses several case studies showing how it can be used to solve more complex problems.