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Recommender Systems - Using Neo4j vs traditional NMF techniques

jariwals
Node Link

Hello,

I see a bunch of articles about how Neo4j could be used to develop recommender systems.
How do recommender systems developed using Neo4j fare in comparison to those developed using NMF (Non-negative Matrix Factorization) techniques?
From my understanding, we can write targeted Cypher queries to get recommendations. But these would be hard-coded queries that work with predefined relations. How would hidden features be discovered and used for giving better recommendations?
I'd really appreciate some discussion regarding the two approaches.

Thanks!

2 REPLIES 2

sameerG
Graph Buddy

Please look into Graph Data Science library for more details on how system works.

anthony_gatlin
Node Clone

This is a great question. I would love to see a legitimate answer.