Semantic Network-Artificial Intelligence Tutorial

Semantic network:-

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.

The structural idea is that knowledge can be stored in the form of graphs, with nodes representing objects in the world, and arcs representing relationships between those objects.

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

Related Other Post

• Expert System in Artificial Intelligence
• Skolemization in Artificial Intelligence
• Horn Clause in Artifiial Intelligence
• A* Search Algorithm
• Best First Search Algorithm

For example, the following:

is intended to represent the data:

• Tom is a cat.
• Tom caught a bird.
• Tom is owned by John.
• Tom is ginger in colour.
• Cats like cream.
• The cat sat on the mat.
• A cat is a mammal.
• A bird is an animal.
• All mammals are animals.
• Mammals have fur.

Semantic Networks Are Majorly Used For

• Representing data
• Revealing structure (relations, proximity, relative importance)
• Supporting conceptual edition
• Supporting navigation

Main Components Of Semantic Networks

1. Lexical component: :-nodes denoting physical objects or links are relationships between objects; labels denote the specific objects and relationships
2. Structural component:- the links or nodes from a diagram which is directed.
3. Semantic component:- Here the definitions are related only to the links and label of nodes, whereas facts depend on the approval areas.
4. Procedural part:- constructors permit the creation of the new links and nodes. The removal of links and nodes are permitted by destructors.

Advantages Of Using Semantic Nets

1. The semantic network is more natural than the logical representation;
2. The semantic network permits using of effective inference algorithm (graphical algorithm)
3. They are simple and can be easily implemented and understood.
4. The semantic network can be used as a typical connection application among various fields of knowledge, for instance, among computer science and anthropology.
5. The semantic network permits a simple approach to investigate the problem space.
6. The semantic network gives an approach to make the branches of related components.

Disadvantages Of Using Semantic Nets

1. There is no standard definition for link names
2. Semantic Nets are not intelligent, dependent on the creator
3. Links are not alike in function or form, confusion in links that asserts relationships and structural links
4. Undistinguished nodes that represent classes and that represents individual objects
5. Links on object represent only binary relations
6. Negation and disjunction  are not easily expressed

Ask question #Pywix

• Facebook Page :- https://www.facebook.com/rgrahulgarg786
• Twitter :- https://twitter.com/rgrahulgarg786
• Instagram:- https://www.instagram.com/rahulgupta.786/
• youTube:- https://www.youtube.com/pywixclasses

Please Like, Comment, Share and Subscribe THANK YOU!