ABSTRACT: Socialmedia sharing websites like Flickr allow users to annotate images with freetags, which significantly contribute to the development of the web imageretrieval and organization. Tag-based image search is an important method tofind images contributed by social users in such social websites. However, howto make the top ranked result relevant and with diversity is challenging. Inthis paper, we propose a social re-ranking system for tag-based image retrievalwith the consideration of images relevance and diversity[1]. We aim atre-ranking images according to their visual information, semantic informationand social clues. The initial results include images contributed by differentsocial users. Usually each user contributes several images. First we sort theseimages by inter-user re-ranking. Users that have higher contribution to thegiven query rank higher. Then we sequentially implement intra-user re-rankingon the ranked users image set, and only the most relevant image from each usersimage set is selected. These selected images compose the final retrievedresults. We build an inverted index structure for the social image dataset toaccelerate the searching process.
Keywords: Conceptual SocialMedia, Tag-based Image Retrieval, Social Clues, Image search, Re-ranking.