Heterogeneous anomaly detection in social diffusion with discriminative feature discovery
文献类型：期刊论文
| 作者 | Liu, Siyuan1; Qu, Qiang2,3; Wang, Shuhui4 |
| 刊名 | INFORMATION SCIENCES
 |
| 出版日期 | 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 |
| WOS记录号 | WOS:000428486600001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 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. |
入库方式： OAI收割
来源：计算技术研究所
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