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An Adaptive Deep Transfer Learning Model for Rumor Detection without Sufficient Identified Rumors

文献类型：期刊论文

作者Guo, Meicheng1; Xu, Zhiwei2,3; Liu, Limin2; Guo, Mengjie3; Zhang, Yujun3
刊名MATHEMATICAL PROBLEMS IN ENGINEERING
出版日期2020-07-17
卷号2020页码:12
ISSN号1024-123X
DOI10.1155/2020/7562567
英文摘要With the extensive usage of social media platforms, spam information, especially rumors, has become a serious problem of social network platforms. The rumors make it difficult for people to get credible information from Internet and cause social panic. Existing detection methods always rely on a large amount of training data. However, the number of the identified rumors is always insufficient for developing a stable detection model. To handle this problem, we proposed a deep transfer model to achieve accurate rumor detection in social media platforms. In detail, an adaptive parameter tuning method is proposed to solve the negative transferring problem in the parameter transferring process. Experiments based on real-world datasets demonstrate that the proposed model achieves more accurate rumor detection and significantly outperforms state-of-the-art rumor detection models.
资助项目National Key Research and Development Program of China[2018YFB1800403] ; National Key Research and Development Program of China[2016YFE0121500] ; National Natural Science Foundation of China[61902382] ; National Natural Science Foundation of China[61972381] ; National Natural Science Foundation of China[61672500] ; National Natural Science Foundation of China[61962045] ; National Natural Science Foundation of China[61502255] ; National Natural Science Foundation of China[61650205] ; Strategic Priority Research Program of Chinese Academy of Science[XDC0203500] ; Natural Science Foundation of Inner Mongolia Autonomous Region[2017MS(LH)0601] ; Natural Science Foundation of Inner Mongolia Autonomous Region[2018MS06003]
WOS研究方向Engineering ; Mathematics
语种英语
WOS记录号WOS:000556227500002
出版者HINDAWI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/15834]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xu, Zhiwei
作者单位1.Inner Mongolia Univ Technol, Coll Informat Engn, Hohhot 100080, Peoples R China
2.Inner Mongolia Univ Technol, Coll Data Sci & Applicat, Hohhot 100080, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Meicheng,Xu, Zhiwei,Liu, Limin,et al. An Adaptive Deep Transfer Learning Model for Rumor Detection without Sufficient Identified Rumors[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020:12.
APA Guo, Meicheng,Xu, Zhiwei,Liu, Limin,Guo, Mengjie,&Zhang, Yujun.(2020).An Adaptive Deep Transfer Learning Model for Rumor Detection without Sufficient Identified Rumors.MATHEMATICAL PROBLEMS IN ENGINEERING,2020,12.
MLA Guo, Meicheng,et al."An Adaptive Deep Transfer Learning Model for Rumor Detection without Sufficient Identified Rumors".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020):12.

入库方式： OAI收割

来源：计算技术研究所

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