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# Yelp18_m1
+ **Dataset description:**
The data statistics are summarized as follows:
| Dataset ID | #Users | #Items | #Interactions | #Train | #Test | Density |
| :-------: | :----: | :----: | :-----------: | :-------: | :-----: | :-----: |
| Yelp18_m1 | 31,668 | 38,048 | 1,561,406 | 1,237,259 | 324,147 | 0.00130 |
+ **Data format:**
user_id item1 item2 ...
+ **Source:** https://www.yelp.com/dataset
+ **Download:** https://huggingface.co/datasets/reczoo/Yelp18_m1/tree/main
+ **RecZoo Datasets:** https://github.com/reczoo/Datasets
+ **Used by papers:**
- Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang. [LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation](https://arxiv.org/abs/2002.02126). In SIGIR 2020.
- Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He. [SimpleX: A Simple and Strong Baseline for Collaborative Filtering](https://arxiv.org/abs/2109.12613). In CIKM 2021.
- Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. [UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation](https://arxiv.org/abs/2110.15114). In CIKM 2021.
+ **Check the md5sum for data integrity:**
```bash
$ md5sum *.txt
520fe559761ff2c654629201c807f353 item_list.txt
0d57d7399862c32152b045ec5d2698e7 test.txt
1b8b5d22a227e01d6de002c53d32b4c4 train.txt
ae4f810cd6e827f10fc418753c7d92f9 user_list.txt
```
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