首页> 外文会议>ACM international conference on information and knowledge management >Mining Direct Antagonistic Communities in Explicit Trust Networks
【24h】

Mining Direct Antagonistic Communities in Explicit Trust Networks

机译:明确信任网络中的直接抗反社

获取原文
获取外文期刊封面目录资料

摘要

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epini-ons, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two sub-communities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging the unique property of direct antagonistic community. We have experimented with synthetic and real data-sets (myGamma and Epinions) to demonstrate the scalability of our proposed solution.
机译:最近有利于分析信任和友谊网络的兴趣,以获得用户之间的关系动态的见解。许多网站,如Epini-Ons,Facebook和其他社交网站允许用户在社区的不同成员之间宣布信任或友谊。在这项工作中,我们有兴趣在涉及信任和不信任的富信托网络中提取直接的敌人社区(DAC)。每个DAC由两个子社区形成,其中每个子社区成员之间的信任关系,但在子社区之间的不信任关系。我们开发了一种高效的算法,可以分析利用直接对抗社区的独特财产的大型信任网络。我们已经尝试了合成和实际数据集(静脉态和渗透)来证明我们提出的解决方案的可扩展性。

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