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HomeHomework Helpcomputer-scienceSemantic Networks

Semantic Networks

Semantic networks are cognitive structures that represent knowledge in the form of interconnected concepts and relationships, often depicted as graphs. They illustrate how information is organized in the mind, with nodes representing concepts and edges indicating the relationships between them.

intermediate
3 hours
Computer Science
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Overview

Semantic networks are powerful tools for representing knowledge in a structured way. They consist of nodes that represent concepts and edges that illustrate the relationships between these concepts. This graphical representation makes it easier to understand complex information and how different ide...

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Key Terms

Node
A point in a semantic network representing a concept or entity.

Example: In a network about animals, 'Dog' could be a node.

Edge
A line connecting two nodes, representing the relationship between them.

Example: An edge might connect 'Dog' and 'Mammal' to show that a dog is a mammal.

Relationship
The connection or association between two nodes.

Example: The relationship 'is a type of' connects 'Sparrow' to 'Bird'.

Ontology
A formal representation of a set of concepts within a domain and the relationships between those concepts.

Example: An ontology for a library might include books, authors, and genres.

Knowledge Representation
The way information and knowledge are structured and stored in a system.

Example: Semantic networks are a form of knowledge representation.

Semantic Web
An extension of the web that enables data to be shared and reused across application, enterprise, and community boundaries.

Example: Using semantic web technologies, data about books can be linked to data about authors.

Related Topics

Knowledge Graphs
Knowledge graphs are a way to store interconnected descriptions of entities, similar to semantic networks but often more complex.
advanced
Artificial Intelligence
AI encompasses various techniques, including semantic networks, to enable machines to mimic human intelligence.
intermediate
Machine Learning
Machine learning involves algorithms that improve automatically through experience, often utilizing semantic networks for data organization.
advanced

Key Concepts

nodesedgesrelationshipsknowledge representation