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"
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"
Code for 2022 Applied Science Special Issue "Logit Averaging: Capturing Global Relation for Session-based Recommendation"
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%.
Amazon KDD Cup '23: Multilingual Recommendation Challenge
Organize AI coding sessions into a searchable knowledge graph using RDF and SPARQL for efficient retrieval and reuse across tools.
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