Using the SemaGrow Stack on top of a recommender system
Channel: Fabrizio
Date: 24/11/2015

The SemaGrow Stack (https://github.com/semagrow/semagrow) allows to federate SPARQL endpoints. It allows to:
- incorporate new data sources with minimal or no back-end software development
- reactively experiment with new relevance and ranking models

In this example we are going to intersect the AGRIS database (http://agris.fao.org) with the crawler database (http://f1000research.com/articles/4-432/v2) and then with the TECA (http://teca.fao.org/) one, using the same recommender system on top of the SemaGrow Stack.