Mining adjacent markets from a large-scale ads video collection for image advertising

Authors:
Guwen Feng;Xin-Jing Wang;Lei Zhang;Wei-Ying Ma
Affiliations:
Nanjing University, Nanjing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China
Venue:
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Year:
2010

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Abstract

The research on image advertising is still in its infancy. Most previous approaches suggest ads by directly matching an ad to a query image, which lacks the power to identify ads from adjacent market. In this paper, we tackle the problem by mining knowledge on adjacent markets from ads videos with a novel Multi-Modal Dirichlet Process Mixture Sets model, which is a unified model of (video frames) clustering and (ads) ranking. Our approach is not only capable of discovering relevant ads (e.g. car ads for a query car image), but also suggesting ads from adjacent markets (e.g. tyre ads). Experimental results show that our proposed approach is fairly effective.