Financial Fraud Detection with Graph Data Science: Augment Your Approach
By David Penick
April 13, 2020 3 mins read
Read blog 1 on how financial services enterprises are using Neo4j’s graph technology to prevent and detect financial fraud.
Explore: community detection algorithms • Financial Fraud Detection • graph data analysis • graph data science • graph database
Graph Algorithms in Neo4j: Triangle Count & Clustering Coefficient
By Jocelyn Hoppa
March 25, 2019 4 mins read
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →
Explore: Clustering Coefficient • community detection algorithms • cypher • global clustering • graph algorithms • Graph Analytics • intelligent solutions • local clustering • Louvain Modularity • Triangle Count
Graph Algorithms in Neo4j: Louvain Modularity
By Jocelyn Hoppa
March 18, 2019 5 mins read
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →
Explore: community detection algorithms • cypher • detecting communities • fraud analytics • graph algorithms • Graph Analytics • intelligent solutions • Louvain Modularity • neo4j • Social Networks
Graph Algorithms in Neo4j: Label Propagation
By Jocelyn Hoppa
March 4, 2019 5 mins read
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • graph database • Knowledge Graph • label propagation • large-scale networks • neo4j
Graph Algorithms in Neo4j: Weakly Connected Components
By Jocelyn Hoppa
February 25, 2019 4 mins read
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • intelligent solutions • Master Data Management • union-find • Weakly Connected Components
Graph Algorithms in Neo4j: Strongly Connected Components
By Jocelyn Hoppa
February 18, 2019 4 mins read
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • Graph Databases • intelligent solutions • Strongly Connected Components