Graph Structure
A Graph Structure is a data structure that represents relationship patterns (through vertex sets and edge connections).
- AKA: Network Structure, Graph Model, Vertex-Edge Structure.
- Context:
- It can (typically) represent Network Elements through vertex nodes.
- It can (typically) capture Element Relationships through edge links.
- It can (typically) model Connection Patterns through graph topology.
- It can (typically) maintain Structural Propertys through graph attributes.
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- It can (often) support Path Analysis through graph traversal.
- It can (often) enable Pattern Discovery through structure analysis.
- It can (often) facilitate Network Visualization through graph layouts.
- It can (often) evolve Network Topology through structure modifications.
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- It can range from being a Simple Graph to being a Complex Graph, depending on its structural complexity.
- It can range from being a Sparse Graph to being a Dense Graph, depending on its edge density.
- It can range from being a Static Structure to being a Dynamic Structure, depending on its change frequency.
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- It can integrate with Graph Algorithms for structure analysis.
- It can utilize Visualization Methods for structure representation.
- It can incorporate Graph Theory for property analysis.
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- Example(s):
- Network Graphs, such as:
- Social Structures, such as:
- System Graphs, such as:
- Technical Structures, such as:
- Data Graphs, such as:
- Information Structures, such as:
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- Network Graphs, such as:
- Counter-Example(s):
- Linear Structure, which lacks network relationships.
- Tree Structure, which prohibits cyclic connections.
- Array Structure, which uses indexed positions.
- See: Graph Theory, Network Model, Data Structure, Network Analysis, Graph Algorithm, Graph-based Data Structure, Graph Data Pattern.