Knowledge Graphs

8.

Advanced Topics

8.1.

Knowledge Graph Embeddings

8.1.1.

Vector Representations

8.1.2.

Entity Embeddings

8.1.3.

Relation Embeddings

8.1.4.

Embedding Models

8.1.4.1.

8.1.4.2.

8.1.4.3.

8.1.4.4.

8.1.5.

8.1.5.1.

Link Prediction

8.1.5.2.

Entity Classification

8.1.5.3.

Similarity Computation

8.2.

Temporal Knowledge Graphs

8.2.1.

Time-Varying Facts

8.2.2.

Temporal Modeling

8.2.3.

Event Representation

8.2.4.

Temporal Reasoning

8.2.5.

Versioning Strategies

8.3.

Quality Assessment

8.3.1.

Accuracy Metrics

8.3.2.

Completeness Measures

8.3.3.

Consistency Checking

8.3.4.

Timeliness Evaluation

8.3.5.

Quality Frameworks

8.4.

Knowledge Graph Evolution

8.4.1.

Change Detection

8.4.2.

Update Propagation

8.4.3.

Version Management

8.4.4.

Migration Strategies

8.5.

Explainability and Provenance

8.5.1.

Provenance Models

8.5.2.

Trust Assessment

8.5.3.

Explanation Generation

8.5.4.

Transparency Methods

8.6.

Machine Learning Integration

8.6.1.

Graph Neural Networks

8.6.2.

Knowledge-Enhanced Learning

8.6.3.

Neuro-Symbolic Approaches

8.6.4.

Previous

7. Applications and Use Cases

Go to top

Next

9. Implementation and Best Practices