Similarity Algorithms¶

Measure similarity between nodes or graphs.

Advanced Feature

Some similarity algorithms are available through the NetworkX adapter for extended functionality.

Using the NetworkX Adapter¶

For advanced similarity measures, use the NetworkX integration:

import grafeo

db = grafeo.GrafeoDB()

# Convert to NetworkX graph
nx_adapter = db.as_networkx(directed=False)
nx_graph = nx_adapter.to_networkx()

# Use NetworkX similarity functions
import networkx as nx

# Jaccard coefficient for potential edges
preds = nx.jaccard_coefficient(nx_graph, [(1, 2), (1, 3)])
for u, v, score in preds:
    print(f"Jaccard({u}, {v}) = {score:.4f}")

Node Similarity via Algorithms API¶

Basic similarity through the algorithms interface:

algs = db.algorithms()

# Use clustering coefficient as a similarity proxy
transitivity = algs.transitivity()

Use Cases¶

Algorithm	Use Case
Jaccard	Set-based comparison
Cosine	Feature-based comparison
Common Neighbors	Link prediction