Knowledge Graph
A Knowledge Graph is a graph structure that represents domain knowledge (through entity relationships and semantic connections).
- AKA: Semantic Knowledge Graph, Entity Graph, Knowledge Network.
- Context:
- It can (typically) store Entity Information through node representations.
- It can (typically) capture Relationship Types through edge labels.
- It can (typically) model Domain Knowledge through graph structures.
- It can (typically) maintain Semantic Context through property annotations.
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- It can (often) support Knowledge Query through graph traversal.
- It can (often) enable Knowledge Inference through pattern matching.
- It can (often) facilitate Knowledge Integration through graph merges.
- It can (often) evolve Knowledge Structure through incremental updates.
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- It can range from being a Domain Specific Graph to being a General Knowledge Graph, depending on its knowledge scope.
- It can range from being a Static Graph to being a Dynamic Graph, depending on its update frequency.
- It can range from being a Simple Graph to being a Complex Graph, depending on its structure complexity.
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- It can integrate with KG Database for data storage.
- It can utilize Graph Algorithms for knowledge discovery.
- It can incorporate Ontology Structures for schema definition.
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- Example(s):
- Enterprise Graphs, such as:
- Business Knowledges, such as:
- Research Graphs, such as:
- Scientific Knowledges, such as:
- Web Graphs, such as:
- Internet Knowledges, such as:
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- Enterprise Graphs, such as:
- Counter-Example(s):
- Relational Database, which uses tabular structure.
- Document Store, which lacks explicit relationships.
- Text Corpus, which contains unstructured data.
- See: Graph Database, Semantic Network, Ontology, Entity Relationship, Knowledge Base.