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Online Multimodal Multiexpert Learning for Social Event Tracking
Shengsheng Qian1,2; Tianzhu Zhang1,2; Changsheng Xu1,2

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.

KeywordSocial Event Tracking Topic Model Social Media Topic Evolution Multimodality
Indexed BySCI
Document Type期刊论文
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
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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