Heterogeneous anomaly detection in social diffusion with discriminative feature discovery

doi:10.1016/j.ins.2018.01.044

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	Heterogeneous anomaly detection in social diffusion with discriminative feature discovery
	Liu, Siyuan 1; Qu, Qiang 2,3; Wang, Shuhui 4
刊名	INFORMATION SCIENCES
	2018-05-01
卷号	439 页码:1-18
关键词	Social networks Anomaly detection Heterogeneous data Diffusion process
ISSN号	0020-0255
DOI	10.1016/j.ins.2018.01.044
英文摘要	Social diffusion is a dynamic process of information propagation within social networks. In this paper, we study social diffusion from the perspective of discriminative features, a set of features differentiating the behaviors of social network users. We propose a new parameter-free framework based on modeling and interpreting of discriminative features that we have created, named HADISD. It utilizes a probability-distribution-based parameter-free method to identify the maximum vertex set with specified features. Using the maximum vertext set, a probability-distribution-based optimization approach is applied to find the minimum number of vertices in each feature category with the maximum discriminative information. HADISD includes an incremental algorithm to update the discriminative vertex set over time. The proposed model is capable of addressing anomaly detection in social diffusion, and the results can be leveraged for both spammer detection and influence maximization. The findings from our extensive experiments on four real-life datasets show the efficiency and effectiveness of the proposed scheme. (C) 2018 Elsevier Inc. All rights reserved.
资助项目	CAS ; MOE Key Laboratory of Machine Perception at Peking University[K-2017-02] ; National Natural Science Foundation of China (NSFC)[61672497] ; National Natural Science Foundation of China (NSFC)[61572488] ; National Natural Science Foundation of China (NSFC)[61673241]
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000428486600001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/5733]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Qu, Qiang
作者单位	1.Penn State Univ, University Pk, PA 16802 USA 2.Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing, Peoples R China 3.Peking Univ, MOE Key Lab Machine Percept, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Siyuan,Qu, Qiang,Wang, Shuhui. Heterogeneous anomaly detection in social diffusion with discriminative feature discovery[J]. INFORMATION SCIENCES,2018,439:1-18.
APA	Liu, Siyuan,Qu, Qiang,&Wang, Shuhui.(2018).Heterogeneous anomaly detection in social diffusion with discriminative feature discovery.INFORMATION SCIENCES,439,1-18.
MLA	Liu, Siyuan,et al."Heterogeneous anomaly detection in social diffusion with discriminative feature discovery".INFORMATION SCIENCES 439(2018):1-18.