Upload Avazu_x1.zip

Avazu_x1.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d87b332da23c5b8c6f472ff73ad8b27a5a698e89afab64b3a56e67b42470b330
+size 624515270

README.md

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+# 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 Details
+
++ **Repository:** https://github.com/reczoo/BARS/tree/main/datasets/Avazu#avazu_x1
+
++ **Used by papers:** 
+    - 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
+      ```