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Argo: intelligent advertising made possible from users' photos

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International Multimedia Conference archive
Proceedings of the seventeen ACM international conference on Multimedia table of contents

Beijing, China

DEMONSTRATION SESSION: Technical demonstrations session 1 table of contents

Pages 957-958

Year of Publication: 2009

ISBN:978-1-60558-608-3

Authors

Xin-Jing Wang	Microsoft Research Asia, Beijing, China
Mo Yu	Harbin Institute of Technology, Harbin, China
Lei Zhang	Microsoft Research Asia, Beijing, China
Wei-Ying Ma	Microsoft Research Asia, Beijing, China

Sponsor

SIGMULTIMEDIA: ACM Special Interest Group on Multimedia

Publisher

ACM New York, NY, USA

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ABSTRACT

Though monetizing user-generated photos has a great potential in image business, this topic is seldom touched due to the difficulties of both image understanding and ads-to-images vocabulary matching. In this technical demonstration, we show case the Argo system, which attempts to monetize UGC (user-generated content) photos by mining a user's interest from a group of his photos and advertising the photos accordingly. Given a page of photos, it first auto-tags each photo by a large-scale search-based image annotation method, then maps both image annotations and the textual descriptions of ads onto an ODP-based topic hierarchy. The mapping produces semantic features which are statistical distributions on ODP topics. Ads are ranked by their similarities to such topic distributions of the photos and the top-ranked ones are output.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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	5	X. J. Wang, L. Zhang, and et al. Annotating images by mining image search results. IEEE Trans. PAMI, 30(11):1919--1932, 2008.