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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Luming Zhang Zimmermann, R. |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore (Luming Zhang; Zimmermann, R.) |
| Abstract | Aesthetic tendency discovery is a useful and interesting application in social media. This paper proposes to categorize large-scale Flickr users into multiple circles. Each circle contains users with similar aesthetic interests (e.g., landscapes or abstract paintings). We notice that: (1) an aesthetic model should be flexible as different visual features may be used to describe different image sets, and (2) the numbers of photos from different users varies significantly and some users have very few photos. Therefore, a regularized topic model is proposed to quantify user's aesthetic interest as a distribution in the latent space. Then, a graph is built to describe the similarity of aesthetic interests among users. Obviously, densely connected users are with similar aesthetic interests. Thus an efficient dense subgraph mining algorithm is adopted to group users into different circles. Experiments show that our approach accurately detects circles on an image set crawled from over 60,000 Flickr users. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 376975 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479970827 |
| DOI | 10.1109/ICME.2015.7177384 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-29 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Communities Integrated circuit modeling Feature extraction Probabilistic logic Clustering algorithms Computational modeling |
| Content Type | Text |
| Resource Type | Article |
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