Unsupervised Machine Learning in Graphs.

Types of graphs:

Apache Jena Fuseki

AWS Neptune

Neo4j

Following are algorithms in unsupervised ML for the following tasks:

**Centrality & Importance**

PageRank

Degree Centrality

Harmonic Centrality

**Pathfinding & Search**

Shortest Path

A* Shortest Path

Minimum Weight Spanning Tree

Random Walk

Breadth & Depth First Search

K-Spanning Tree

**Similarity**

Node Similarity

K-Nearest Neighbors KNN

Cosine Similarity (Word2Vec)

**Graph Embeddings**

Node2Vec

FastRP

GraphSAGE

**Heuristic Link**

Adamic Adar

Common Neighbors

Total Neighbors

**Community Detection**

Triangle Count

Local Clustering Coefficient