Knowledge Commons of Institute of Automation,CAS
Boosted Multi-modal Supervised Latent Dirichlet Allocation for Social Event Classification | |
Shengsheng Qian![]() ![]() ![]() | |
2014-08 | |
会议名称 | International Conference on Pattern Recognition |
会议日期 | August 24-28, 2014 |
会议地点 | Stockholm, Sweden |
摘要 | With the rapidly increasing popularity of Social Media sites (e.g., Flickr, YouTube, and Facebook), it is convenient for users to share their own comments on many social events, which successfully facilitates social event generation, sharing and propagation and results in a large amount of user-contributed media data (e.g., images, videos, and texts) for a wide variety of real-world events of different types and scales. As a consequence, it has become more and more difficult to find exactly the interesting events from massive social media data, which is useful to browse, search and monitor social events by users or governments. To deal with these issues, we propose a novel boosted multi-modal supervised Latent Dirichlet Allocation (BMM-SLDA) for social event classification. Our BMM-SLDA has a number of advantages. (1) It can effectively exploit the multi-modality and the supervised information of social events jointly. (2) It is suitable to large-scale data analysis by utilizing boosting weighted sampling strategy to iteratively select a small subset data to efficiently train the corresponding topic models. (3) It effectively exploits boosting document weight distribution by classification error, and can iteratively learn new topic model to correct the previously misclassified documents. We evaluate our BMM-SLDA on a real-world dataset and show extensive results, which show that our model outperforms state-of-the-art methods. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14791 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
通讯作者 | Changsheng Xu |
作者单位 | National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Shengsheng Qian,Tianzhu Zhang,Changsheng Xu. Boosted Multi-modal Supervised Latent Dirichlet Allocation for Social Event Classification[C],2014. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
ICPR14_BMMSLDA for E(1087KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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