Semantic Graphs and RDF
- (Vanderbilt University)
- Overview
A semantic graph is a graph model and knowledge representation that uses nodes and edges to represent knowledge. It also captures the meaning of that knowledge in a structured form that can be used for reasoning and inference.
In artificial intelligence (AI), a semantic network is a knowledge representation technique for organizing and storing knowledge. It's a type of graphical model that shows the relationships between concepts, ideas, and objects in a way that is easy for humans to understand.
Semantic knowledge graphs can provide significant benefits for structuring and analyzing large amounts of aggregated data across diverse heterogeneous sources. They can also facilitate inference from data and generation of insights for several purposes.
- Semantic Graphs and Resource Description Framework (RDF)
The standard way to represent semantic graphs is RDF (Resource Description Framework) - a directed graph described as triples. A triple in an RDF graph has three components:
- Node for the subject
- An arc with the predicate linking the subject to the object
- Node for the object
According to Wikipedia, a semantic graph is "a network representing semantic relations between concepts...it is a directed or undirected graph consisting of vertices representing concepts and edges representing semantic relations between concepts."
