Semantic Network in Artificial Intelligence

A semantic network is a graphic notation for representing knowledge in patterns of interconnected nodes. Semantic networks became popular in artificial intelligence and natural language processing only because it represents knowledge or supports reasoning. These act as another alternative for predicate logic in a form of knowledge representation.

1. Semantic nets consist of nodes, links and link labels. In these networks diagram, nodes appear in form of circles or ellipses or even rectangles which represents objects such as physical objects, concepts or situations.
2. Links appear as arrows to express the relationships between objects, and link labels specify relations.
3. Relationships provide the basic needed structure for organizing the knowledge, so therefore objects and relations involved are also not needed to be concrete.
4. Semantic nets are also referred to as associative nets as the nodes are associated with other nodes

For example, the following:

Semantic Networks Are Majorly Used For

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Main Components Of Semantic Networks

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Advantages Of Using Semantic Nets

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Disadvantages Of Using Semantic Nets

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Originally published at https://pywix.blogspot.com.