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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoguang Rui Nenghai Yu Jimin Jia Mingjing Li |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of EEIS, Univ. of Sci. & Technol. of China, Hefei (Xiaoguang Rui; Nenghai Yu; Jimin Jia) |
| 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. |
| Starting Page | 113 |
| Ending Page | 116 |
| File Size | 256079 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424425709 |
| DOI | 10.1109/ICME.2008.4607384 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-23 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cultural differences Search engines Image retrieval Communities Computational modeling Visualization Image edge detection large scale static rank bipartite graph virtual community |
| Content Type | Text |
| Resource Type | Article |
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