CASIA OpenIR  > 类脑智能研究中心
Spam Short Messages Detection via Mining Social Networks
Jianyun Liu; Yuhang Zhao; Zhaoxiang Zhang; Yunhong Wang; Xuemei Yuan; Lei Hu; Zhenjiang Dong
Source PublicationJournal of Computer Science and Technology
2012-05-19
Volume27Issue:3Pages:506-514
AbstractShort message service (SMS) is now becoming an indispensable way of social communication, and the problem of mobile spam is getting increasingly serious. We propose a novel approach for spam messages detection. Instead of conventional methods that focus on keywords or flow rate filtering, our system is based on mining under a more robust structure: the social network constructed with SMS. Several features, including static features, dynamic features and graph features, are proposed for describing activities of nodes in the network in various ways. Experimental results operated on real dataset prove the validity of our approach.
KeywordSpam Detection Social Network Graph Mining
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13225
Collection类脑智能研究中心
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
GB/T 7714
Jianyun Liu,Yuhang Zhao,Zhaoxiang Zhang,et al. Spam Short Messages Detection via Mining Social Networks[J]. Journal of Computer Science and Technology,2012,27(3):506-514.
APA Jianyun Liu.,Yuhang Zhao.,Zhaoxiang Zhang.,Yunhong Wang.,Xuemei Yuan.,...&Zhenjiang Dong.(2012).Spam Short Messages Detection via Mining Social Networks.Journal of Computer Science and Technology,27(3),506-514.
MLA Jianyun Liu,et al."Spam Short Messages Detection via Mining Social Networks".Journal of Computer Science and Technology 27.3(2012):506-514.
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