Hey there,
I'm currently leading a project that is tasked with finding appropriate gifts for people based on a few descriptive inputs :like interests, hobbies, budget, age, gender, bio, relationship, etc.
I currently don't have an official dataset, but I'm going around scraping different websites and their items - think like Amazon or aliexpress, but in much smaller quantity (around 1k unique items)
After getting this data though, I'm not sure what my next step ideally should be.
My mind is hovering around using an LLM go generate tags or something like a perfect profile (a perfect profile is basically a fake user that has hobbies, budget, age, gender, bio, relationship but is optimized by the LLM go be perfectly suited for the item) per item. Then, I would embed that data into a vector DB, and for real queries, I would query in the vector DB for similar profiles or tags and retrieve the closest result.
I would greatly appreciate any suggestions or techniques I can use to better optimize this process or rethink it altogether.
Thank you very much for your time ❤️