The current work deals with the problem of attempting to predict the popularity of images before even being uploaded. This method is specifically focused on Flickr images. Social features of each image as well as that of the user who had uploaded it, have been recorded. The dataset also includes the engagement score of each image which is the ground truth value of the views obtained by each image over a period of 30 days. The work aims to predict the popularity of images on Flickr over a period of 30 days using the social features of the user and the image, as well as the visual features of the images. The method states that the engagement sequence of an image can be said to depend on two independent quantities, namely scale and shape of an image. Once the shape and scale of an image have been predicted, combining them the predicted sequence of an image over 30 days is obtained. The current work follows a previous work done in the same direction, with certain speculations and suggestions of improvement.
翻译:目前的工作涉及试图预测图像在上传前的受欢迎程度的问题。这种方法特别侧重于Flickr图像。每个图像的社会特征以及上传图像的用户的社会特征已经记录下来。数据集还包括每张图像的接触评分,这是每张图像在30天内获得的视图的地面真实价值。工作的目的是利用用户的社会特征和图像以及图像的视觉特征预测Flickr上图像在30天内的受欢迎程度。方法指出,图像的接触序列可以说取决于两个独立的数量,即图像的规模和形状。一旦预测了图像的形状和规模,就可以将30天内的图像的预测序列结合起来。目前的工作遵循了以前在同样方向上完成的工作,并提出了一些改进的猜测和建议。