Demographic Attribute Inference from Social Multimedia Behaviors: a Cross-OSN Approach | |
Liancheng Xiang1,2; Jitao Sang1,2; Changsheng Xu1,2 | |
2017 | |
会议日期 | January 4-6, 2017 |
会议地点 | Reykjavik, Iceland |
关键词 | Cross-osn Stable Demographic Attribute Inference Dynamic Behavior |
DOI | 10.1007/978-3-319-51811-4_42 |
英文摘要 |
This study focuses on exploiting the dynamic social multimedia behaviors to infer the stable demographic attributes. Existing demographic attribute inference studies are devoted to developing advanced features/models or exploiting external information and knowledge. The conflicts between dynamicity of behaviors and the steadiness of demographic attributes are largely ignored. To address this issue, we introduce a cross-OSN approach to discover the shared stable patterns from users' social multimedia behaviors on multiple Online Social Networks (OSNs). The basic assumption for the proposed approach is that, the same user's cross-OSN behaviors are the reflection of his/her demographic attributes in different scenarios. Based on this, a coupled projection matrix extraction method is proposed for solution, where the cross-OSN behaviors are collectively projected onto the same space for demographic attribute inference. Experimental evaluation is conducted on a self-collected Google+ and Twitter dataset consisting of four types of demographic attributes as gender, age, relationship and occupation. The experimental results demonstrate the effectiveness of cross-OSN based demographic attribute inference. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/14447] |
专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
通讯作者 | Changsheng Xu |
作者单位 | 1.National Lab of Pattern Recognition, Institute of Automation, CAS, Beijing 100190, China 2.University of Chinese Academy of Sciences, Beijing 100049, China |
推荐引用方式 GB/T 7714 | Liancheng Xiang,Jitao Sang,Changsheng Xu. Demographic Attribute Inference from Social Multimedia Behaviors: a Cross-OSN Approach[C]. 见:. Reykjavik, Iceland. January 4-6, 2017. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论