Institute of Computing Technology, Chinese Academy IR
| Online web video topic detection and tracking with semi-supervised learning | |
| Li, Guorong1; Jiang, Shuqiang2; Zhang, Weigang3; Pang, Junbiao4; Huang, Qingming1,2 | |
| 2016-02-01 | |
| 发表期刊 | MULTIMEDIA SYSTEMS
 |
| ISSN | 0942-4962 |
| 卷号 | 22期号:1页码:115-125 |
| 摘要 | With the pervasiveness of online social media and rapid growth of web data, a large amount of multi-media data is available online. However, how to organize them for facilitating users' experience and government supervision remains a problem yet to be seriously investigated. Topic detection and tracking, which has been a hot research topic for decades, could cluster web videos into different topics according to their semantic content. However, how to online discover topic and track them from web videos and images has not been fully discussed. In this paper, we formulate topic detection and tracking as an online tracking, detection and learning problem. First, by learning from historical data including labeled data and plenty of unlabeled data using semi-supervised multi-class multi-feature method, we obtain a topic tracker which could also discover novel topics from the new stream data. Second, when new data arrives, an online updating method is developed to make topic tracker adaptable to the evolution of the stream data. We conduct experiments on public dataset to evaluate the performance of the proposed method and the results demonstrate its effectiveness for topic detection and tracking. |
| 关键词 | Topic detection and tracking Web video Multi-feature fusion Semi-supervised learning |
| DOI | 10.1007/s00530-014-0402-0 |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | China Postdoctoral Science Foundation[2012M520436] ; National Basic Research Program of China (973 Program)[2012CB316400] ; National Natural Science Foundation of China[61303153] ; National Natural Science Foundation of China[61025011] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[61322212] ; National Natural Science Foundation of China[61202234] ; National Natural Science Foundation of China[61202322] ; Present Foundation of UCAS |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Information Systems ; Computer Science, Theory & Methods |
| WOS记录号 | WOS:000368828500011 |
| 出版者 | SPRINGER |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://119.78.100.204/handle/2XEOYT63/8911 |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Li, Guorong; Zhang, Weigang; Huang, Qingming |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 3.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150006, Peoples R China 4.Beijing Univ Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Guorong,Jiang, Shuqiang,Zhang, Weigang,et al. Online web video topic detection and tracking with semi-supervised learning[J]. MULTIMEDIA SYSTEMS,2016,22(1):115-125. |
| APA | Li, Guorong,Jiang, Shuqiang,Zhang, Weigang,Pang, Junbiao,&Huang, Qingming.(2016).Online web video topic detection and tracking with semi-supervised learning.MULTIMEDIA SYSTEMS,22(1),115-125. |
| MLA | Li, Guorong,et al."Online web video topic detection and tracking with semi-supervised learning".MULTIMEDIA SYSTEMS 22.1(2016):115-125. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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