Semantic Knowledge Graphing Finds Application in Several Problem Solving Applications, Including Business Intelligence, Internet Marketing, and Complex Systems Analysis
Semantic Knowledge Graphing (SKG) is integration of information into an ontology. The term knowledge graph was first introduced by Google in 2012. A knowledge graph acquires and integrates information into an ontology and applies a reasoner to derive new knowledge. SKG encodes knowledge graphs, or knowledge trees, and associated infrastructures such as knowledge bases, knowledge databases, and knowledge bases used in high semantic associations (such as those underlying natural language processing and image processing models).
The knowledge graph provides a structure for representing the meaning of sentences in an object-oriented language such as English. This framework was originally developed at the University of Sydney, Australia, by professors Richard Lazarus and John Heard. In its earliest form, Semantic Knowledge Graphing , used data from a large-scale experiment in the Australian wool market, showed that the price difference in price could be predicted from the purchase history of a particular item. From the initial studies, knowledge graph representation formed the basis for SKG and has now been further developed to incorporate a wide range of problem solving applications, including business intelligence, internet marketing, complex systems analysis, e-business, financial markets, and social networks.
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