Introduction to Semantic Networks
Semantic networks represent knowledge in the form of nodes (representing concepts or objects) and links (representing relationships between concepts). They provide a graphical representation of knowledge that is easy to understand and manipulate.
Nodes, Arcs, and Hierarchical Structure
Semantic networks consist of nodes connected by arcs, where nodes represent concepts or objects and arcs represent relationships between them. Semantic networks often have a hierarchical structure, with nodes organized into levels representing increasingly abstract or general concepts.
Examples and Applications
Semantic networks have been used in various applications, including knowledge representation in expert systems, natural language understanding, cognitive modelling, and ontological engineering.
Advantages and Disadvantages
Semantic networks provide a flexible and intuitive representation of knowledge that is easy to understand and manipulate. However, they may struggle with representing complex relationships or capturing the uncertainty inherent in real-world knowledge.