首页> 外文会议>IEEE International Conference on Big Data and Smart Computing >Analysis of Behavior Patterns to Identify Nicknames of a User in Online Community
【24h】

Analysis of Behavior Patterns to Identify Nicknames of a User in Online Community

机译:在在线社区中识别用户昵称的行为模式分析

获取原文

摘要

An online community is a virtual group that is mediated through the Internet for users to share interests and hobbies. Unlike social network service (SNS), an online community is an anonymous service mainly based on nickname. Some users exploit this anonymity and conduct malicious activities. Actions should be taken to filter these users and limit their activities. One problem lies in that nicknames are frequently changed in online communities, and automatically filtering nicknames is difficult when they are constantly malicious. Another problem is data fragmentation in which the data of the same user exists under different nicknames due to the first problem. Therefore, to solve these issues, we propose a behavior pattern feature vector, which considers online community characteristics and identifies nicknames of the same user. Specifically, we propose a method to identify nicknames of the same user using actual data of an online community in Korea.
机译:在线社区是通过互联网调解的虚拟组,供用户分享兴趣和爱好。与社交网络服务(SNS)不同,在线社区主要基于昵称,是匿名服务。有些用户利用这种匿名和进行恶意活动。应采取行动过滤这些用户并限制他们的活动。一个问题在于,昵称经常在在线社区中更改,并且当他们不断恶意时,自动过滤昵称很难。另一个问题是数据碎片,其中由于第一问题,同一用户的数据存在于不同的绰号下。因此,为了解决这些问题,我们提出了一种行为模式特征向量,其考虑在线社区特征并识别同一用户的昵称。具体地,我们提出了一种使用韩国在线社区的实际数据来识别同一用户的昵称。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号