In this talk we'll explore some of the innate properties of (social) graphs from fields like anthropology and sociology. By understanding the forces and tensions within the graph structure, we'll be able to predict how the graph will evolve over time. In turn we'll apply these powerful techniques to modelling domains in Neo4j (a graph database) and show how Neo4j can be used to drive business intelligence using both techniques like graph algorithms and predictive techniques from graph theory. Don't worry, there won't be too much maths either :-) Talk objectives: to show the audience how a few simple, well-known properties of graphs can be used to power some impressive predictive analytics from a connected data set. Target audience: Broadly two categories: 1. Data scientists 2. Developers who want insight into their customer behaviour, especially around social recommendations.

No outline is available