论文标题
“你先用眼睛吃饭”：优化Yelp图像广告
"You eat with your eyes first": Optimizing Yelp Image Advertising
论文作者
论文摘要
企业的在线摄影表现可以在其成功或失败中发挥至关重要的作用。我们使用Yelp的图像数据集和基于星星的审查系统来衡量图像在促进业务方面的有效性。预处理Yelp数据集后，我们使用转移学习来训练一个接受Yelp图像并预测星星评价的分类器。此外，我们然后训练一个gan，以定性地研究高效图像的共同特性。我们在分类各种图像类别的简化星级评分时达到了90-98％的精度，并观察到包含蓝天，开放环境和许多窗口的图像与更高的Yelp评论相关。
A business's online, photographic representation can play a crucial role in its success or failure. We use Yelp's image dataset and star-based review system as a measurement of an image's effectiveness in promoting a business. After preprocessing the Yelp dataset, we use transfer learning to train a classifier which accepts Yelp images and predicts star-ratings. Additionally, we then train a GAN to qualitatively investigate the common properties of highly effective images. We achieve 90-98% accuracy in classifying simplified star ratings for various image categories and observe that images containing blue skies, open surroundings, and many windows are correlated with higher Yelp reviews.
