Graphs & Unsupervised Machine Learning

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