Graph Algorithms: Predict Real-World Behavior by Jennifer Reif

Learn how graph algorithms can help you predict real-world behavior and why an averages approach fails to describe group dynamics. We will start with an overview of which algorithms in Neo4j to apply for various types of optimal paths, influence in a network, and community detection. We will also discuss use cases that span across industries including recommendations, resiliency planning, fraud prevention, and traffic engineering/routing (such as IP and call). This will come alive through a live demo, where we look at what kinds of information you can retrieve and decisions you can make based on results from different algorithms and sets of data.

From this session, you will gain the knowledge to recognize whether you have a graph analytics problem and how you can get started.