Netemb: Network Embedding Datasets

Multiple real-world network and graph datasets categorized for network embedding research. The collection includes various graph structures representing relational connectivity and topological patterns in real-world systems.

Use Cases

• Train node embedding models using the graph adjacency structures
• Evaluate link prediction algorithms on the network edge connectivity
• Benchmark graph representation learning using the provided real-world topologies

Strengths

• Includes real-world network graphs
• Features graph-based data formats
• Contains connectivity data for network embedding