arXiv abstracts recommender based on specific user preferences about recnn

[awarebayes]

Yes, it works with everything, so long as you can transform it into a vector.
About the authors: I would choose like top 5000 and encode them categorically somehow. Plenty of encodings: category -> vector
You can also search the papers which they wrote and create some NLP representation of the authors by titles. (Mean of BERT output)
About multiple categories: same answer applies
I would also consider obtaining BERT representations of the abstracts
Also consider doing something like that with the title.
Then you just merge together and apply PCA to all the vectors to get something dimensionally meaningful like 128 / 256 / 512
If you have user interactions (i.e. ratings of article by a given user), RecNN can be used for learning and recommendation.

But if you want to find a similar article, then just use Faiss / Milvus on these vectors, no learning needed

Thanks @awarebayes for your quick reply :-)

Would you help me to implement that for https://paper2code.com ? It would be awesome for highlighting your work on RecNN.

If you wanna discuss about it privately, here is my telegram handle deepocrates.

Cheers,
X

[awarebayes]

I do not think you need a learning based recommendation since you do not have any ratings
You do not need to use RecNN
Just make vectors and use Faiss with Milvis
Milvus is docker based and is super easy to set up

Hi,

The thing is paper2code is matching the repositories per papers so we have the stars as rating.

Eg.
Paper page: https://paper2code.com/paper/164402/image-super-resolution-with-cross-scale-non-local-attention-and-exhaustive-self-exemplars-mining
Code page: https://paper2code.com/code/github.com/SHI-Labs/Cross-Scale-Non-Local-Attention

That's why I posted the issue. Sorry that I forgot to introduce that.

Cheers,
X

[awarebayes]

It focuses on Reinforcement Learning for personalized news recommendation

One person is not personalized. Also it is not sequential
But I got an idea for you:
Create a github parser and parse people's profiles for github stars for respective papers, use it as user ratings, timestamps can make in sequential
Sorry, you would have to do the parsing part yourself
Upon accomplishing that, feel free to write me a question concerning the library on [email protected], or open a github issue