I think that the main issue is less the technique (although… yes, please use RL if you can) and more the lack of data. Browsing gives very little insight: dwell-time is a poor proxy for interest, and mixes horrid ideas that are so bad they are worth sharing with friends and confusing photos where you need to squint to figure out if it’s what you are looking for.
Both e-commerce and social media are really not good at gathering express feedback for what people want and valuing that expressly. Please, let me tell you that I did spend time looking at this thread about the latest reality TV scandal but I don‘t want to hear about it ever again! Please, let me tag options as “maybe” or let me tell you what you’d need to change for me to buy that shirt. Public, performative Likes and Favourite lists that are instantly reactivation spam-fodder… Come on, you know better.
I used to work for a big e-commerce site (the leading site for 18-25 y.o. females). We had millions of references (really) and it was a problem. The search team had layers upon layers of ranking algos, incredible papers at conference… but still, low impact on conversion. It was more than anything else that we could do, but nowhere as transformative as it could be. Instead, I suggested copying the Tinder interaction in a companion app:
* left, never see that item again;
* right, add it to a long list of stuff you might want to revisit. We probably would have to separate that from the Favourite list to avoid clutter, but maybe not, to make that selection worthwhile.
The learning you could get from that dataset, even with a basic RL algo to queue suggestions… People thought it was “too much” which I’m still bitter about.
Both e-commerce and social media are really not good at gathering express feedback for what people want and valuing that expressly. Please, let me tell you that I did spend time looking at this thread about the latest reality TV scandal but I don‘t want to hear about it ever again! Please, let me tag options as “maybe” or let me tell you what you’d need to change for me to buy that shirt. Public, performative Likes and Favourite lists that are instantly reactivation spam-fodder… Come on, you know better.
I used to work for a big e-commerce site (the leading site for 18-25 y.o. females). We had millions of references (really) and it was a problem. The search team had layers upon layers of ranking algos, incredible papers at conference… but still, low impact on conversion. It was more than anything else that we could do, but nowhere as transformative as it could be. Instead, I suggested copying the Tinder interaction in a companion app:
* left, never see that item again;
* right, add it to a long list of stuff you might want to revisit. We probably would have to separate that from the Favourite list to avoid clutter, but maybe not, to make that selection worthwhile.
The learning you could get from that dataset, even with a basic RL algo to queue suggestions… People thought it was “too much” which I’m still bitter about.