首页> 外国专利> USE OF SOCIAL INTERACTIONS TO PREDICT COMPLEX PHENOMENA

USE OF SOCIAL INTERACTIONS TO PREDICT COMPLEX PHENOMENA

机译:利用社交互动预测复杂现象

摘要

Systems and methods for using social network information to predict complex phenomena. According to one embodiment the system or method comprises a Support Vector Machine classifier utilized to infer a pre-determined state of an individual, location, or event based on information gathered from a social network dataset. A conditional random field model can then be used to predict an individual's propensity toward that pre-determined state using features derived from the social network dataset. Performance of the conditional random field model can be enhanced by including features that are not only based on the status of net work connections, but are also based on the estimated encounters with individuals having the pre-determined state, including individuals other than network connections.
机译:使用社交网络信息预测复杂现象的系统和方法。根据一个实施例,该系统或方法包括支持向量机分类器,其被用于基于从社交网络数据集中收集的信息来推断个人,位置或事件的预定状态。然后,可以使用条件随机字段模型,使用从社交网络数据集中获取的特征来预测个人对该预定状态的倾向。通过包含不仅基于网络连接状态的特征,而且还基于与具有预定状态的个人(包括网络连接以外的个人)的估计遭遇,可以增强条件随机字段模型的性能。

著录项

  • 公开/公告号US2015170296A1

    专利类型

  • 公开/公告日2015-06-18

    原文格式PDF

  • 申请/专利权人 UNIVERSITY OF ROCHESTER;

    申请/专利号US201314413722

  • 发明设计人 HENRY KAUTZ;ADAM SADILEK;

    申请日2013-07-09

  • 分类号G06Q50;G06Q10;

  • 国家 US

  • 入库时间 2022-08-21 15:26:20

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

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