Title :
SocialRank: A ranking model for web image retrieval in web 2.0
Author :
Rui, Xiaoguang ; Yu, Nenghai ; Jia, Jimin ; Li, Mingjing
Author_Institution :
Dept. of EEIS, Univ. of Sci. & Technol. of China, Hefei
fDate :
June 23 2008-April 26 2008
Abstract :
In this paper, we proposed an image ranking model called SocialRank for Web image search engine, which leverages rich metadata and structures of virtual communities in online photo-sharing sites in Web 2.0. In SocialRank, three levels of static rankings for sites, users and images are computed, respectively. To achieve combined image rankings in a site, a graph model is proposed to integrate social relations between users and images to reinforce their static rankings. To obtain the unified image rankings of different sites, image rankings are normalized and combined by considering duplicate images and static site rankings. The diversity of search results is also an important factor of image search engines. So we proposed an offline static diversity ranking of images. The experimental results show that the proposed SocialRank performs comparably with Google image search.
Keywords :
Internet; graph theory; image retrieval; meta data; search engines; SocialRank; Web 2.0; graph model; image ranking model; image retrieval; metadata; search engine; Asia; Bipartite graph; Content based retrieval; Cultural differences; Explosives; Image retrieval; Laboratories; Large-scale systems; Multimedia computing; Search engines; bipartite graph; large scale; static rank; virtual community;
Conference_Titel :
Multimedia and Expo, 2008 IEEE International Conference on
Conference_Location :
Hannover
Print_ISBN :
978-1-4244-2570-9
Electronic_ISBN :
978-1-4244-2571-6
DOI :
10.1109/ICME.2008.4607384
