Basically I'm developing a recommendation system using a graph database (specifically neo4j), and I want to apply recommendation algorithms. Since i'm using a graph database, I can see the recommendation problem as a graph problem, and intuitively i can use graph based algorithms for the recommendation system.From my research, recommendation systems are a subclass of information filtering system that seek to predict the rating or preference that a user would give to an item. And there exists basically two types, collaborative filtering and content based. I've done a research on the algoritms, and i found some interesting ones:Weighted Bipartite Graph algorithmEnergy Spread ActivationUnion ColorsMy question is simple, which other graph algorithms exists that can be used for graph based recommendation system? Or if I use a graph database for recommendation system, the algorithm doesn't necessary need to be a graph based?Thanks. Any suggestions are welcomed.
Which algorithms should I use for recommendation system using a graph database?
predictive modeling;algorithms;graphs;recommender system;neo4j