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README.md

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 # SIGIR23-VGCL
-Tensorflow implementation of our SIGIR 2023 accepted paper "Generative-Contrastive Graph Learning for Recommendation"
+Implementation of our SIGIR 2023 accepted paper "Generative-Contrastive Graph Learning for Recommendation", PDF file is: https://le-wu.com/files/Publications/CONFERENCES/SIGIR-23-yang.pdf
+
+In this work, we investigate GCL-based recommendation from the perspective of better contrastive view construction, and propose a
+novel Variational Graph Generative-Contrastive Learning (VGCL) framework. Instead of data augmentation, we leverage the variational
+graph reconstruction technique to generate contrastive views to serve contrastive learning. Specifically, we first estimate each node’s
+probability distribution by graph variational inference, then generate contrastive views with multiple samplings from the estimated
+distribution. As such, we build a bridge between the generative and contrastive learning models for recommendation. The advantages
+have twofold. First, the generated contrastive representations can well reconstruct the original graph without information distortion.
+Second, the estimated variances vary from different nodes, which can adaptively regulate the scale of contrastive loss for each node.
+Furthermore, considering the similarity of the estimated distributions of nodes, we propose a cluster-aware twofold contrastive
+learning, a node-level to encourage consistency of a node’s contrastive views and a cluster-level to encourage consistency of nodes
+in a cluster. Empirical studies on three public datasets clearly show the effectiveness of the proposed framework.
+
+Prerequisites
+-------------
+* Please refer requirements.txt
+
+Usage
+-----
+python run_VGCL.py --dataset douban_book
+
+Citation
+--------
+If you find this useful for your research, please kindly cite the following paper:<br>
+```
+@article{VGCL2023,
+  title={Generative-Contrastive Graph Learning for Recommendation},
+  author={Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou and Meng Wang}
+  jconference={46nd International ACM SIGIR Conference on Research and Development in Information Retrieval},
+  year={2023}
+}
+```
+
+Author contact:
+--------------
+Email: yyh.hfut@gmail.com
+