On the selection of trending image from the web
The recommendation of trending images has become a popular feature used by commercial search engines to attract public attention. By browsing through trending images, search engine users can discover trending events at a glance. However, the selection of trending images is very challenging and remains an open issue. Most existing work is highly dependent on editorial efforts, though some preliminarily identify a few plain features for trending images. In this paper, we investigate a set of perceptual factors that can distinguish trending images from common ones. We propose a set of trending-aware features based on several common criteria, which reflect the characteristics of trending images. We further construct a manually labeled dataset based on a commercial search engine's query log over a two-week timespan. We evaluate our proposed method on this dataset and the results demonstrate its effectiveness.