reczoo/Frappe_x1
收藏资源简介：
# 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](https://ojs.aaai.org/index.php/AAAI/article/view/5768) 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 | + **Source:** https://www.baltrunas.info/context-aware + **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](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. + **Check the md5sum for data integrity:** ```bash $ md5sum train.csv valid.csv test.csv ba7306e6c4fc19dd2cd84f2f0596d158 train.csv 88d51bf2173505436d3a8f78f2a59da8 valid.csv 3470f6d32713dc5f7715f198ca7c612a test.csv ```
# Frappe_x1 + **数据集描述：** Frappe数据集是一份上下文感知的应用使用日志，包含957位用户在各类场景下使用4082款应用产生的96203条记录。该数据集共包含10个特征字段，分别为用户ID（user_id）、物品ID（item_id）、时段（daytime）、星期几（weekday）、是否周末（isweekend）、学习场景（homework）、消费等级（cost）、天气（weather）、国家（country）以及城市（city）。目标值用于表征用户是否在当前场景下使用了对应应用。遵循自适应因子分解网络（Adaptive Factorization Network，简称AFN）的相关研究工作，我们将数据集按照7:2:1的比例随机划分为训练集、验证集与测试集。 数据集统计信息如下： | 数据集划分 | 总样本数 | 训练集样本数 | 验证集样本数 | 测试集样本数 | | :--------: | :-----: |:-----: | :----------: | :----: | | Frappe_x1 | 288,609 | 202,027 | 57,722 | 28,860 | + **来源：** https://www.baltrunas.info/context-aware + **下载地址：** https://huggingface.co/datasets/reczoo/Frappe_x1/tree/main + **代码仓库：** https://github.com/reczoo/Datasets + **被引用论文：** - 程伟宇, 沈妍妍, 黄麟鹏. 自适应因子分解网络：学习自适应阶数特征交互[C]//AAAI 2020. 2020. - 毛科龙, 朱杰明, 苏良才, 蔡国浩, 李雨儒, 董振华. FinalMLP：面向点击率（Click-Through Rate，简称CTR）预测的增强双流MLP模型[C]//AAAI 2023. 2023. - 朱杰明, 贾庆林, 蔡国浩, 戴全宇, 李静杰, 董振华, 唐瑞明, 张锐. FINAL：面向点击率（Click-Through Rate，简称CTR）预测的因子化交互层模型[C]//SIGIR 2023. 2023. + **数据完整性MD5校验：** bash $ md5sum train.csv valid.csv test.csv ba7306e6c4fc19dd2cd84f2f0596d158 train.csv 88d51bf2173505436d3a8f78f2a59da8 valid.csv 3470f6d32713dc5f7715f198ca7c612a test.csv
Frappe_x1 数据集概述
数据集描述
Frappe 数据集包含一个上下文感知的应用使用日志，共有 96203 条记录，涉及 957 名用户和 4082 个应用。数据集包含 10 个特征字段，包括 user_id、item_id、daytime、weekday、isweekend、homework、cost、weather、country、city。目标值表示用户在特定上下文中是否使用了该应用。根据 AFN 的研究，数据集被随机分为 7:2:1 的比例，分别作为训练集、验证集和测试集。
数据集统计
| 数据集划分 | 总数 | 训练集 | 验证集 | 测试集 |
|---|---|---|---|---|
| Frappe_x1 | 288,609 | 202,027 | 57,722 | 28,860 |
使用该数据集的论文
- 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.
数据完整性检查
bash $ md5sum train.csv valid.csv test.csv ba7306e6c4fc19dd2cd84f2f0596d158 train.csv 88d51bf2173505436d3a8f78f2a59da8 valid.csv 3470f6d32713dc5f7715f198ca7c612a test.csv
