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Implementation of "Pre-training Graph Transformer with Multimodal Side Information for Recommendation"

Dockerfile 0.57% Python 85.23% Jupyter Notebook 11.61% Shell 2.59%
deep-learning graph-transformer machine-learning multi-modal-learning python pytorch recommendation

pmgt's Introduction

PMGT

Implementation of "Pre-training Graph Transformer with Multimodal Side Information for Recommendation" (MM'21)

Experiments

Datasets Metrics Top-N Recommendation CTR Prediction
GMF MLP NeuMF NeuMF-PMGT DCN DCN-PMGT
VG
N@10 0.1426 0.0972 0.1621 0.1810 - -
N@20 0.1602 0.1209 0.1815 0.2067 - -
R@10 0.2057 0.1724 0.2365 0.2748 - -
R@20 0.2687 0.2592 0.3060 0.3661 - -
AUC - - - - 0.8178 0.8667
TG
N@10 0.1730 0.1163 0.1995 0.2192 - -
N@20 0.1837 0.1369 0.2189 0.2384 - -
R@10 0.2104 0.1828 0.2733 0.2889 - -
R@20 0.2497 0.2589 0.3445 0.3590 - -
AUC - - - - 0.8387 0.8486

Stats

Datasets Data for Downstream tasks Item Graph Multimodal Feat.
# Users # Items # Interact. # Nodes # Edges # Visual Feat. # Textual Feat.
VG 27,988 6,551 98,278 7,252 88,606 502 7,252
TG 134,697 10,337 378,138 10,834 38,252 1,279 10,834

Log

[2022.01.16]

  • Add TG dataset & experiment

[2022.01.15]

[2022.01.14]

  • Experiment for NeuMF-PMGT

[2022.01.13]

  • Implement PMGT pre-training

[2022.01.12]

[2022.01.11]

  • Implement Graph structure reconstruction loss (pmgt/pmgt/models.py)
  • Implement Node feature reconstruction loss

[2022.01.10]

[2022.01.09]

[2022.01.08]

  • HPO for NCF (VG dataset)

[2022.01.07]

  • Implment NCF Training
  • Experiment on VG dataset over NCF Baseline (except NeuMF-pre)

[2022.01.06]

  • Report stats for VG dataset
  • Implement NCF Dataset
  • Implement NDCG@k
  • Implement Recall@k

[2022.01.05]

  • Implement Item Graph
  • Implement NCF

[2022.01.04]

[2022.01.03]

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pmgt's Issues

instructions of running pmgt model

Hi, can you give some instructions for us to run the code? I have downloaded the dataset and done the preprocessing to get the correct format. But not sure how to run the pmgt model. Thanks!

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