Social Photo Tagging Recommendation Using Community-Based Group Associations

2012 IEEE International Conference on Multimedia and Expo Workshops Pub Date : 2012-07-09 DOI:10.1109/ICMEW.2012.46

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

{"title":"Social Photo Tagging Recommendation Using Community-Based Group Associations","authors":"Chien-Li Chou, Yee-Choy Chean, Yi-Cheng Chen, Hua-Tsung Chen, Suh-Yin Lee","doi":"10.1109/ICMEW.2012.46","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Multimedia and Expo Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2012.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

Abstract

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.

查看原文本刊更多论文

社会照片标签推荐使用社区为基础的团体协会

在社交网络中，生活照片占据了网页内容的很大一部分。为了与出现在其中的人分享照片，用户必须手动标记他们的名字，社交网络系统会立即将照片链接到这些人。然而，当人们在日常生活中拍摄成千上万的照片时，手动标记照片是一项耗时的任务。因此，如何为照片推荐标签成为越来越多研究者关注的问题。在本文中，我们的目标是为带有一个标记脸的查询照片推荐标签。我们融合了人脸识别的结果和从社会背景中获得的用户关系。此外，还提出了基于社区的组关联(CBGA)，通过社区检测来发现用户之间的组关联。最后，实验结果表明，将人脸识别与社会关系相结合，提高了照片标签推荐的性能。此外，该框架还实现了高质量的社交照片标签推荐。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2012 IEEE International Conference on Multimedia and Expo Workshops

自引率

0.00%

发文量