Code repo for Lightweight Embeddings for Graph Collaborative Filtering (LEGCF)

• The paper can be found here.
• Accepted by SIGIR'24.
• Code structure adopted from LightGCN.

Dataset

• Train and test sets of Gowalla, Yelp2020 and Amazon-book are located in here.

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Quick Start

Run program with Gowalla dataset with bucket size 500, 2 compositional meta-embeddings/entity on cuda device 0:

python3 engine.py --dataset_name gowalla --num_clusters 500 --num_composition_centroid 2 --device_id 0

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Implementation Details

1. Gowalla

   Hyperparam	Value
   GCN layer	3
   l2 penalty factor	5
   lr	1e-3
   assignment update freq $m$	every epoch
   #composition embs per entity $t$	2
   #clusters $c$	500
   init anchor weight $w^*$	0.5

2. Yelp2020

   Hyperparam	Value
   GCN layer	4
   l2 penalty factor	5
   lr	1e-3
   assignment update freq $m$	every epoch
   #composition embs per entity $t$	2
   #clusters $c$	500
   init anchor weight $w^*$	0.6

3. Amazon-book

   Hyperparam	Value
   GCN layer	4
   l2 penalty factor	5
   lr	1e-3
   assignment update freq $m$	every epoch
   #composition embs per entity $t$	2
   #clusters $c$	500
   init anchor weight $w^*$	0.9