Knowledge Commons of Institute of Automation,CAS
Online Multimodal Multiexpert Learning for Social Event Tracking | |
Shengsheng Qian1,2; Tianzhu Zhang1,2; Changsheng Xu1,2 | |
发表期刊 | IEEE TRANSACTIONS ON MULTIMEDIA |
2018 | |
卷号 | 20期号:10页码:2733-2748 |
摘要 | In this paper, we aim to automatically identify and track the interesting social event from vast amounts of social media data. However, there are two existing challenges: 1) how to model multimodal social event data over time and visualize the topic evolution and 2) how to alleviate the tracking drift problem to boost social event tracking accuracy. We propose a novel online multimodal multiexpert learning algorithm for social event tracking. Compared with existing methods, the proposed model has several advantages: First, it has a nonparametric online multimodal tracking module, which is able to not only automatically learn the number of topics from data over time, but also exploit the multimodal property of the social event. Second, it adopts a novel multiexpert minimization restoration scheme and allows the tracked model to evolve backwards to undo undesirable model updates, which helps alleviate the model drift problem of social event tracking. Third, it is able to not only effectively track the multimodal social event, but also automatically exploit the topic evolution of the social event for a deep understanding with multimodal topics. To evaluate the proposed model, we collect a real-world dataset for research on social event tracking with multimodality information. We have conducted extensive experiments, and both qualitative and quantitative evaluation results have demonstrated the effectiveness of the proposed model. |
关键词 | Social Event Tracking Topic Model Social Media Topic Evolution Multimodality |
收录类别 | SCI |
语种 | 英语 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/25805 |
专题 | 学术期刊 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 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. Online Multimodal Multiexpert Learning for Social Event Tracking[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(10):2733-2748. |
APA | Shengsheng Qian,Tianzhu Zhang,&Changsheng Xu.(2018).Online Multimodal Multiexpert Learning for Social Event Tracking.IEEE TRANSACTIONS ON MULTIMEDIA,20(10),2733-2748. |
MLA | Shengsheng Qian,et al."Online Multimodal Multiexpert Learning for Social Event Tracking".IEEE TRANSACTIONS ON MULTIMEDIA 20.10(2018):2733-2748. |
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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 | ||
Online Multimodal Mu(4742KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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