Social Photo Tagging Recommendation Using Community-Based Group Associations

Chien Li Chou, Yee-Choy Chean, Yi Cheng Chen, Hua-Tsung Chen, Suh-Yin Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


In the social network, living photos occupy a large portion of web contents. For sharing a photo with the people appearing in that, users have to manually tag the people with their names, and the social network system links the photo to the people immediately. However, tagging the photos manually is a time-consuming task while people take thousands of photos in their daily life. Therefore, more and more researchers put their eyes on how to recommend tags for a photo. In this paper, our goal is to recommend tags for a query photo with one tagged face. We fuse the results of face recognition and the user's relationships obtained from social contexts. In addition, the Community-Based Group Associations, called CBGA, is proposed to discover the group associations among users through the community detection. Finally, the experimental evaluations show that the performance of photo tagging recommendation is improved by combining the face recognition and social relationship. Furthermore, the proposed framework achieves the high quality for social photo tagging recommendation.
Original languageAmerican English
Title of host publicationIEEE International Conference on Multimedia and Expo Workshops (ICMEW)
Number of pages6
StatePublished - 2012

Publication series

Name IEEE International Conference on Multimedia and Expo Workshops
ISSN (Print)2330-7927


  • social network; social context; face recognition; photo tagging recommendation

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