Frappe_x1
Dataset description:
The Frappe dataset contains a context-aware app usage log, which comprises 96203 entries by 957 users for 4082 apps used in various contexts. It has 10 feature fields including user_id, item_id, daytime, weekday, isweekend, homework, cost, weather, country, city. The target value indicates whether the user has used the app under the context. Following the AFN work, we randomly split the data into 7:2:1 as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset Split Total #Train #Validation #Test Frappe_x1 288,609 202,027 57,722 28,860 Download: https://huggingface.co./datasets/reczoo/Frappe_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. 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. 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. In SIGIR 2023.
Check the md5sum for data integrity:
$ md5sum train.csv valid.csv test.csv ba7306e6c4fc19dd2cd84f2f0596d158 train.csv 88d51bf2173505436d3a8f78f2a59da8 valid.csv 3470f6d32713dc5f7715f198ca7c612a test.csv