工业组合广告问题数据集

工业组合广告问题数据集是为包容性金融而创建的，旨在通过组合广告策略帮助金融科技平台向特定未服务人群提供低息贷款。数据集包含用户特征、应用程序活动记录等加密和处理过的个人信息，以及广告渠道的成本和效果预测。该数据集用于训练和评估预测优化模型，以最大化网络应用用户的整体转化率，解决预算分配和个性化广告决策问题。

The Industrial Combined Advertising Problem Dataset was created for inclusive finance, designed to help fintech platforms offer low-interest loans to specific underserved populations through combined advertising strategies. The dataset encompasses encrypted and processed personal information including user features and application activity records, alongside cost and effectiveness predictions for advertising channels. This dataset is utilized for training and evaluating predictive optimization models, with the objective of maximizing the overall conversion rate of web application users and addressing challenges related to budget allocation and personalized advertising decision-making.