  The thumbnail, as the first sight of a micro-video, plays a pivotal role in
attracting users to click and watch. Although several pioneer efforts have been
dedicated to jointly considering the quality and representativeness for
selecting the thumbnail, they are limited in exploring the influence of users`
interests. While in the real scenario, the more the thumbnails satisfy the
users, the more likely the micro-videos will be clicked. In this paper, we aim
to select the thumbnail of a given micro-video that meets most users`
interests. Towards this end, we construct a large-scale dataset for the
micro-video thumbnails. Ultimately, we conduct several baselines on the dataset
and demonstrate the effectiveness of our dataset.
