NEO4J User Group: CASE STUDY: Using Graph Theory & Graph Databases to understand User Intent
Event Info
Description
We are in a Graph Renaissance period. The advent of high-performance free/open-source software combined with inexpensive Cloud computing platforms enable graphs of information to be manipulated and utilised at scales never before seen. While use-cases like mining social and web data with graphs are common-place, their use in Natural Language Processing has largely been overlooked. In this presentation Michael Cutler will describe how TUMRA have used graph-based NLP algorithms as a core component of their upcoming digital marketing product TUMRA Optimize.
Michael is the CTO co-founder of TUMRA, a Data Science startup based in Chiswick, West London. First discovering Hadoop back in 2008, Michael has been following the bleeding edge of ‘Big Data’ technology since before it was called ‘Big Data’ and has applied it to solve real-world problems. Before starting TUMRA, Michael was a senior researcher in the R&D labs for British Sky Broadcasting, inventing new technologies and solutions for everything from Satellite, Video and Network systems through to Web and Mobile-based applications.
