concept

Semantic Networks

Semantic networks are a knowledge representation technique in artificial intelligence and cognitive science that uses a graph structure to model relationships between concepts or entities. They consist of nodes representing objects, concepts, or events, connected by edges that define semantic relationships such as 'is-a', 'part-of', or 'has-property'. This approach helps in organizing and reasoning about knowledge in a human-like, intuitive way, often used for natural language processing, information retrieval, and expert systems.

Also known as: Semantic Nets, Conceptual Graphs, Knowledge Graphs, Semantic Graphs, Semantic Webs
🧊Why learn Semantic Networks?

Developers should learn semantic networks when working on AI projects involving knowledge representation, natural language understanding, or ontology development, as they provide a structured way to encode domain knowledge. They are particularly useful in building chatbots, recommendation systems, and semantic search engines, where understanding relationships between concepts is crucial for accurate reasoning and inference.

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