July 17, 2026· ~7 min readRecommendation Engines with Neo4j Knowledge Graphs: From Cypher to Production ## Why Graphs for Recommendations? Recommendation engines have traditionally been dominated by matrix factorisation (Singular Value Decomposition, A
July 15, 2026· ~7 min readFraud Detection with Graph Databases: Patterns, Algorithms, and Production Architectures ## Why Graphs for Fraud Detection? Fraud is fundamentally relational. A synthetic identity shares a phone number with a known bad actor. A credit ca
July 15, 2026· ~7 min readBuilding Graph-Based Recommendation Systems with Neo4j ## Why Graphs for Recommendations? Most recommendation systems start with a matrix: users as rows, items as columns, and interaction signals (purcha
July 12, 2026· ~8 min readGraph Algorithms in Practice with Neo4j: PageRank, Shortest Path, and Community Detection # Graph Algorithms in Practice with Neo4j: PageRank, Shortest Path, and Community Detection Graph theory exists on a spectrum. At one end is the pur
July 12, 2026· ~10 min readGraph Data Modeling with Neo4j: Patterns, Anti-Patterns, and Pragmatic Design # Graph Data Modeling with Neo4j: Patterns, Anti-Patterns, and Pragmatic Design Graph databases promise flexible schemas and intuitive data models.
July 11, 2026· ~10 min readGraph Algorithms in Production with Neo4j GDS ## Why Graph Algorithms in Production? Graph databases excel at storing and querying relationships, but the real value emerges when you analyse the