In the last post, I talked about creating the enhanced DocGraph dataset using Mortar and Neo4J. Our data model looks like the following: Nodes Organizations Specialties Providers Locations CountiesZip Census Relationships * Organizations -[:PARENT_OF] – Providers -[:SPECIALTY]- Specialties * Providers -[:LOCATED_IN]-Locations * Providers -[:REFERRED]-Providers * Counties -[:INCOME_IN]- CountiesZip * Locations – [:LOCATED_IN]-Locations Each of the […]
Month: August 2013
Building an Enhanced DocGraph Dataset using Mortar (Hadoop) and Neo4J
“The average doctor has likely never heard of Fred Trotter, but he has some provocative ideas about using physician data to change how healthcare gets delivered.” This was from a recent Gigaom article. You can read more details about DocGraph from Fred Trotter’s post. The basic data set is just three columns: two separate NPI […]
Recommender Tips, Mortar and DocGraph
Jonathan Packer wrote on Mortar’s blog about flexible recommender models. Jonathan articulates that “from a business perspective the two most salient advantages of graph-based models: flexibility and simplicity.” Some of salient points made in the article are: graph-based models are modular and transparent simple graph-based model will allow you to build a viable recommender system […]