Upload README.md

README.md

@@ -1,21 +1,28 @@
 # Avazu_x1
 
-This dataset contains about 10 days of labeled click-through data on mobile advertisements. It has 22 feature fields including user features and advertisement attributes. We provide the reusable, processed dataset released by [the BARS benchmark](https://openbenchmark.github.io), which are randomly split into 7:1:2 as the training set, validation set, and test set, respectively. 
++ **Dataset description:**
 
-### Dataset Details
+  This dataset contains about 10 days of labeled click-through data on mobile advertisements. It has 22 feature fields including user features and advertisement attributes. The preprocessed data are randomly split into 7:1:2\* as the training set, validation set, and test set, respectively. 
 
-+ **Repository:** https://github.com/reczoo/BARS/tree/main/datasets/Avazu#avazu_x1
+  The dataset statistics are summarized as follows:
+
+  | Dataset  | Total | #Train | #Validation | #Test | 
+  | :--------: | :-----: |:-----: | :----------: | :----: | 
+  | Avazu_x1 |  40,428,967     | 28,300,276   |  4,042,897     |  8,085,794    |     
+
++ **Source:** https://www.kaggle.com/c/avazu-ctr-prediction/data
++ **Download:** https://huggingface.co/datasets/reczoo/Avazu_x1/tree/main
++ **Repository:** https://github.com/reczoo/Datasets
 
 + **Used by papers:** 
+    - Weiyu Cheng, Yanyan Shen, Linpeng Huang. [Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions](https://ojs.aaai.org/index.php/AAAI/article/view/5768). In AAAI 2020.
     - Kelong Mao, Jieming Zhu, Liangcai Su, Guohao Cai, Yuru Li, Zhenhua Dong. [FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction](https://arxiv.org/abs/2304.00902). In AAAI 2023.
     - Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang. [FINAL: Factorized Interaction Layer for CTR Prediction](https://dl.acm.org/doi/10.1145/3539618.3591988). In SIGIR 2023.
-    - Weiyu Cheng, Yanyan Shen, Linpeng Huang. [Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions](https://ojs.aaai.org/index.php/AAAI/article/view/5768). In AAAI 2020.
 
 + **Check the md5sum for data integrity:**
-
-      ```bash
-      $ md5sum train.csv valid.csv test.csv
-      f1114a07aea9e996842c71648e0f6395  train.csv
-      d9568f246357d156c4b8030fadb8b623  valid.csv
-      9e2fe9c48705c9315ae7a0953eb57acf  test.csv
-      ```
+    ```bash
+    $ md5sum train.csv valid.csv test.csv
+    f1114a07aea9e996842c71648e0f6395  train.csv
+    d9568f246357d156c4b8030fadb8b623  valid.csv
+    9e2fe9c48705c9315ae7a0953eb57acf  test.csv
+    ```