Paper resources for Neural Network based content filtering

Are there any links to recommended research (papers, articles, etc.) for content based filtering leveraging neural networks?

There are many results if we google “content based filtering neural network” or search particularly in google scholar. This one, for example, looks like a review and was cited quite a number of times.


Here is a repo with many Recommendation System Papers. You might be interested in the Deep Learning section.

Also I’m part of a public discord group for MLOps run by Chip Huyen that has a RecSys section and really nice people to answer questions specifically about Recommendation Systems.

Check them out here! MLOps (@chipro)

thanks you have a well curated list here. I will check out the discord and ask additional questions there.

thanks I looked up some papers on my own as well (meta/facebook has some interesting recent ones) but was curious about the particular approach demonstrated in the course.

For example theory around the dot product of embedding vs concatenating them into a ‘final network’. Or vs learning embedding separately then concatenating into a vector. I am sure all of this has been tried or has a theoretical issue which is why I was curious for any resources around the method shown in the lecture.

@gennt, I see. I was not in the process of deciding which approach to adopt for the lab. We will have to wait for someone who knows about it.