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网络水军识别研究
引用本文:莫倩,杨珂.网络水军识别研究[J].软件学报,2014,25(7):1505-1526.
作者姓名:莫倩  杨珂
作者单位:北京工商大学 计算机与信息工程学院, 北京 100048;北京工商大学 计算机与信息工程学院, 北京 100048
基金项目:国家自然科学基金(61170112);北京市属高等学校高层次人才引进与培养计划(CIT&TCD201304034);民政部减灾和应急工程重点实验室开放基金(LDRERE20120105)
摘    要:网络水军识别关键技术已成为当前数据挖掘领域最为活跃的研究之一.如何挖掘海量用户信息中潜藏的网络水军特征与行为模式,从而发现网络水军,以维护良好的网络环境,保障合理的网络秩序,已成为一项十分具有挑战性的工作.对比传统与新型网络水军识别研究,从识别特征角度对近几年内网络水军识别研究进展进行综述,对其关键技术和效用评价进行了前沿概括、比较和分析,并对网络水军识别中有待深入研究的难点和发展趋势进行了展望.

关 键 词:网络水军识别  社交网络水军  电子商务水军  邮件水军  水军机器人
收稿时间:2013/6/14 0:00:00
修稿时间:4/9/2014 12:00:00 AM

Overview of Web Spammer Detection
MO Qian and YANG Ke.Overview of Web Spammer Detection[J].Journal of Software,2014,25(7):1505-1526.
Authors:MO Qian and YANG Ke
Affiliation:School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China
Abstract:With its rising popularity, as evidenced in social networks, online shopping platforms and email systems, detection of Web spammer has already become one of the hottest topics in the data mining field. The main challenge of Web spammer detection is how to recognize spammer behavior patterns by examining spammer features and attributes from big dataset in order to limit the proliferation of Internet spam and insure quality of Internet service. This paper presents an overview of Web spammer detection, along with a comparison over the difference between traditional and burgeoning spammer detection approaches. The key techniques and evaluation methods are classified and discussed from several aspects. At last, the prospects for future development and suggestions for possible extensions are emphasized.
Keywords:Web spammer detection  social network spammer  online shopping Websites spammer  E-mail spammer  spam bot
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