Yelp has been running the Yelp Dataset challenge since 2013, a competition that encourages people to explore and research Yelp’s open dataset. The Yelp dataset represents real data that is very well structured and highly interconnected, and is therefore perfectly suited for graph analytics.
In this talk we’ll show how to use various algorithms from the Neo4j Graph Algorithms Library to navigate business categories, order search results based on user similarities, find relevant reviews using Personalised PageRank, and build a photo based gallery recommendation engine.
ABOUT THE SPEAKERS
William Lyon – Neo4j – Developer Relations Engineer
Along with his work as Developer Relations Engineer at Neo4j, Will also heads up the Neo4j Data Journalism Accelerator Program. (https://neo4j.com/graph-database-data-journalism-accelerator-program/). Prior to joining Neo4j, William worked as software developer for several startups in the real estate, quantitative finance and predictive API spaces. William holds a Masters degree in Computer Science from the University of Montana.
Mark Needham – Neo4j – Developer Relations Engineer
Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in Neo4j 3.1. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com. He tweets at @markhneedham.
We’ll be taking questions live during the session, but if you have any questions before or after be sure to post them in the project’s thread in the Neo4j Community Site (https://community.neo4j.com/t/exploring-yelp-with-graph-algorithms/3456).
09:00 PST (UTC – 8 hours)
12:00 EST (UTC – 5 hours)
19:00 CEST (UTC + 2 hours)
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