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Show HN: Personal Recommendation Engine with Graph Neural Networks(data-science-blog.com)

232 points by data_scientist_guy 1 year ago | flag | hide | 16 comments

  • john_doe 1 year ago | next

    Great work! I've been playing around with GNNs as well and I'm really impressed with the performance.

    • jane_doe 1 year ago | next

      Thanks! GNNs definitely provide a new perspective when it comes to recommendation engines. I think they have a lot of potential.

  • nerd_king 1 year ago | prev | next

    I'm having a bit of trouble understanding the implementation. Is there any chance you could provide a more detailed explanation or tutorial?

    • jane_doe 1 year ago | next

      Sure! I'll put together a more detailed tutorial and post it on my website as soon as I can.

  • meme_lover 1 year ago | prev | next

    Will this work for recommending memes too? :P

    • jane_doe 1 year ago | next

      Haha. In theory, it could be modified to work for that kind of data. It might just require some tweaking of the input features and evaluation metrics.

  • ml_questions 1 year ago | prev | next

    I'm not super familiar with graph neural networks. Could someone explain how this implementation differs from a traditional neural network?

    • job_seeker 1 year ago | next

      In a traditional neural network, the inputs and outputs are vectors. But in a graph neural network, the inputs and outputs are graphs. This type of architecture allows the model to perform computations over the graph structure, which is particularly useful for tasks like recommendation where relationships/interactions/similarity between entities need to be captured.

  • data_scientist 1 year ago | prev | next

    Some type of leaderboard / evaluation online where users vs users can recommend against each other would be fun! Maybe this could encourage better curation than the current algo.

    • sci_guy 1 year ago | next

      I agree. I think it would be really interesting to see how different users' recommendations stack up against each other. Maybe a 'tournament' style mode could be implemented.

  • newbie 1 year ago | prev | next

    I'm writing a recommendation engine for a personal project; do you think this technology can benefit me? If so, where do I get started?

    • jane_doe 1 year ago | next

      Yes, I definitely think it could benefit you! The implementation itself can be quite complex, so I'd recommend reading up on graph neural networks and playing around with some smaller examples first. Once you feel comfortable, you can start integrating it into your recommendation engine project.

  • code_wiz 1 year ago | prev | next

    This is cool. Mind if I use this for my thesis project?

    • jane_doe 1 year ago | next

      Of course! Just make sure to properly cite the original work and give credit where it's due. Good luck with your thesis!

  • engineer_bob 1 year ago | prev | next

    It seems like you're using some kind of stochastic gradient descent-like algorithm in order to update the parameters? Could you confirm / explain further?

    • jane_doe 1 year ago | next

      Yes, you're correct. The parameters of the GNN are updated using a variant of stochastic gradient descent called Adam. I've found that it has a good trade-off between convergence speed and computational complexity. I also experimented with RProp and Momentum, but those didn't turn out to be as stable comparatively.