session-based-recommendation

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"

Recommender Systems Paperlist that I am interested in

Session-based Recommendation

[SIGIR 2020] Python implementation for "TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation"

PyTorch Implementation of Introducing Self-Attention to Target Attentive Graph Neural Networks (AISP '22)

[ECIR 2024] Official repository for the paper titled "Self Contrastive Learning for Session-based Recommendation"

Comparative study of Graph Attention Networks for graph-based session recommendation.

A session-based recommendation system to recommend baby products on Amazon using 4 models namely ITEMKNN, POP, GRU4Rec, and STAMP, STAMP performs the best in all accuracy metrics followed by GRU4Rec. We also did result analysis, including ranking accuracy, coverage, popularity.

Two-stage session-based recommender (LightGBM LambdaRank) for an Inditex hackathon. Cold-start focused, 93% of sessions have no user history. NDCG@5 = 0.377, Hit Rate@5 = 76%.

Code for 2022 Applied Science Special Issue "Logit Averaging: Capturing Global Relation for Session-based Recommendation"

This repository contains my summaries of various academic papers I have read.

Data and feedback-loop half of a session-based music recommender on Navidrome — live scrobbler events, versioned datasets for GRU4Rec/SessionKNN, and drift-triggered retraining.

Amazon KDD Cup '23: Multilingual Recommendation Challenge

OTTO session-based recommendation — co-visitation baseline + SASRec multi-task transformer