I am working on recommendation system on different articles using tensorflow. I have built content based, collaborative filtering and popularity based recommender models. Now I am working on location based reommender model. But I stuck on how to build such like recommnder model using tensorflow.
My approach was to filter different articles by using users location and then apply content based, collborative filtering and popularity based models.
Is there anyone that give me some tips about this recommender models?
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Any reason not to simply include the location as a context feature in the model input? Then your model could learn associations between locations and the articles that users like.
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I can filter articles with locaton and apply popularity, content based and collaborative filtering methods. But it seems in efficient.
I’m trying to implement content-based filtering with Tensorflow Recommender (TFRS). So if you built you content based system with TFRS, can you please help me understand how I can do the same?
Sorry that I can’t help you with your request, but on a contrary asking you for the help