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[P] I built SRec.ai, a Steam video game recommender (details on comment) (srec.ai)

submitted 10 months ago by ilos-vigil@alien.top to c/machinelearning@academy.garden

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[–] ilos-vigil@alien.top 1 points 10 months ago

May I ask you what stack do you use?

Stack for which part (model training, front-end, back-end or something else)? Anyway, i find Torch, TorchServe, PostgreSQL and NextJS are vital part of the project.

Also, for the ML part, why did you choose this model?

Do you mean GCE-GNN as smart recommender? If so, these are primary reasons (copied from SRec blog page),

User-free model, but utilize other user's sequence during prediction. By user-free model, I mean the model doesn't use user ID/representation on prediction. It's a required feature for SRec recommender system since all visitor is anonymous.
Authors of GCE-GNN provide source code of the model. This saves some time to re-implement GCE-GNN or verify different GCE-GNN implementations (such as RecBole-GNN) by myself.
GCE-GNN model architecture/framework is relatively easy to understand.

What I dislike with NN is that they provide black box recommendations while users would like to understand WHY results are recommended

As user, sometimes i also feel this. That's why i also create recommendation by game tags which show some explanation.