CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
Multi-Modal Event Topic Model for Social Event Analysis
Qian, Shengsheng1; Zhang, Tianzhu1; Xu, Changsheng; Shao, Jie2
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
2016-02-01
Volume18Issue:2Pages:233-246
SubtypeArticle
AbstractWith the massive growth of social events in Internet, it has become more and more difficult to exactly find and organize 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 this problem, we propose a novel multi-modal social event tracking and evolution framework to not only effectively capture multi-modal topics of social events, but also obtain the evolutionary trends of social events and generate effective event summary details over time. To achieve this goal, we propose a novel multi-modal event topic model (mmETM), which can effectively model social media documents, including long text with related images, and learn the correlations between textual and visual modalities to separate the visual-representative topics and non-visual-representative topics. To apply the mmETM model to social event tracking, we adopt an incremental learning strategy denoted as incremental mmETM, which can obtain informative textual and visual topics of social events over time to help understand these events and their evolutionary trends. To evaluate the effectiveness of our proposed algorithm, we collect a real-world dataset to conduct various experiments. Both qualitative and quantitative evaluations demonstrate that the proposed mmETM algorithm performs favorably against several state-of-the-art methods.
KeywordEvent Evolution Multi-modality Social Event Tracking Social Media Topic Model
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TMM.2015.2510329
WOS KeywordMULTIMEDIA ; TRACKING ; RETRIEVAL ; TEXT
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Indexed BySCI
Language英语
Funding OrganizationNational Basic Research Program of China(2012CB316304) ; National Natural Science Foundation of China(61225009 ; Beijing Natural Science Foundation(4131004) ; 61432019 ; 61572498 ; 61303173 ; 61532009 ; 61472115 ; 61472379 ; U1435211 ; 61572296)
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000368402400008
Citation statistics
Cited Times:32[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10673
Collection模式识别国家重点实验室_多媒体计算与图形学
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Elect Sci & Technol, Sch Comp Sci & Engn, Big Media Comp Ctr, Chengdu 610051, Peoples R China
Recommended Citation
GB/T 7714
Qian, Shengsheng,Zhang, Tianzhu,Xu, Changsheng,et al. Multi-Modal Event Topic Model for Social Event Analysis[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2016,18(2):233-246.
APA Qian, Shengsheng,Zhang, Tianzhu,Xu, Changsheng,&Shao, Jie.(2016).Multi-Modal Event Topic Model for Social Event Analysis.IEEE TRANSACTIONS ON MULTIMEDIA,18(2),233-246.
MLA Qian, Shengsheng,et al."Multi-Modal Event Topic Model for Social Event Analysis".IEEE TRANSACTIONS ON MULTIMEDIA 18.2(2016):233-246.
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