In this talk we'll explore powerful analytic techniques for graph data. Firstly we'll discover some of the innate properties of (social) graphs from fields like anthropology and sociology. By understanding the forces and tensions within the graph structure and applying some graph theory, we'll be able to predict how the graph will evolve over time. To test just how powerful and accurate graph theory is, we'll also be able to (retrospectively) predict World War 1 based on a social graph and a simple algorithm. Then we'll see how graph matching can be used to extract online business intelligence (for powerful retail recommendations). In turn we'll apply these powerful techniques to modelling domains in Neo4j (a graph database) and show how Neo4j can be used to make sense of connected data demanding online scenarios. Don't worry, there won't be much maths :-)
- To have fun! And learn some reactive and predictive analytics techniques from graph theory and Neo4j.
- Fun people! Curious people. Data people.
Dr. Jim Webber is Chief Scientist with Neo Technology the company behind the popular open source graph database Neo4j, where he where he works on R&D for highly scalable graph databases and writes open source software. Jim has written two books on integration and distributed systems: “Developing Enterprise Web Services” on XML Web Services and “REST in Practice” on using the Web for building large-scale systems. His latest book is “Graph Databases” which focuses on the Neo4j database. His blog is located at http://jimwebber.org and he tweets often @jimwebber.