公开(公告)号：US09693086B2

公开(公告)日：2017-06-27

申请号：US14949442

申请日：2015-11-23

Applicant: INVIDI TECHNOLOGIES CORPORATION

Inventor： Michael Kouritzin ,  Surrey Kim ,  Jarett Hailes ,  Patrick M. Sheehan ,  Alden Lloyd Peterson ,  Earl Cox

IPC: G06N5/00 ,  G06F1/00 ,  H04N21/2668 ,  H04N21/442 ,  G06Q30/02 ,  H04H60/45 ,  H04H20/10 ,  H04N21/25 ,  H04N21/258 ,  H04N21/466 ,  H04N21/81 ,  H04H60/63

CPC classification number: H04N21/2668 ,  G06Q30/02 ,  H04H20/106 ,  H04H60/45 ,  H04H60/63 ,  H04N21/252 ,  H04N21/25883 ,  H04N21/44222 ,  H04N21/4661 ,  H04N21/4665 ,  H04N21/4667 ,  H04N21/812

Abstract: A targeted advertising system selects an asset (e.g., ad) for a current user of a user equipment device (e.g., a digital set top box in a cable network). The system can first operate in a learning mode to receive user inputs and develop evidence that can characterize multiple users of the user equipment device audience. In a working mode, the system can process current user inputs to match a current user to one of the identified users of that user equipment device audience. Fuzzy logic and/or stochastic filtering may be used to improve development of the user characterizations, as well as matching of the current user to those developed characterizations. In this manner, targeting of assets can be implemented not only based on characteristics of a household but based on a current user within that household.

公开(公告)号：US20160142754A1

公开(公告)日：2016-05-19

申请号：US14949442

申请日：2015-11-23

Applicant: INVIDI TECHNOLOGIES CORPORATION

Inventor： Michael Kouritzin ,  Surrey Kim ,  Jarett Hailes ,  Patrick M. Sheehan ,  Alden Lloyd Peterson ,  Earl Cox

IPC: H04N21/2668 ,  H04N21/81 ,  H04N21/258 ,  H04N21/25 ,  H04N21/442 ,  H04N21/466

CPC classification number: H04N21/2668 ,  G06Q30/02 ,  H04H20/106 ,  H04H60/45 ,  H04H60/63 ,  H04N21/252 ,  H04N21/25883 ,  H04N21/44222 ,  H04N21/4661 ,  H04N21/4665 ,  H04N21/4667 ,  H04N21/812

Abstract: A targeted advertising system selects an asset (e.g., ad) for a current user of a user equipment device (e.g., a digital set top box in a cable network). The system can first operate in a learning mode to receive user inputs and develop evidence that can characterize multiple users of the user equipment device audience. In a working mode, the system can process current user inputs to match a current user to one of the identified users of that user equipment device audience. Fuzzy logic and/or stochastic filtering may be used to improve development of the user characterizations, as well as matching of the current user to those developed characterizations. In this manner, targeting of assets can be implemented not only based on characteristics of a household but based on a current user within that household.

公开(公告)号：US20130254787A1

公开(公告)日：2013-09-26

申请号：US13663780

申请日：2012-10-30

Applicant: INVIDI TECHNOLOGIES CORPORATION

Inventor： Earl Cox ,  Patrick M. Sheehan ,  Alden Lloyd Peterson ,  Michael Kouritzin ,  Surrey Kim ,  Jarett Hailes

IPC: H04N21/442

CPC classification number: H04N21/2668 ,  G06Q30/02 ,  H04H20/106 ,  H04H60/45 ,  H04H60/63 ,  H04N21/252 ,  H04N21/25883 ,  H04N21/44222 ,  H04N21/4661 ,  H04N21/4665 ,  H04N21/4667 ,  H04N21/812

Abstract: A targeted advertising system selects an asset (e.g., ad) for a current user of a user equipment device (e.g., a digital set top box in a cable network). The system can first operate in a learning mode to receive user inputs and develop evidence that can characterize multiple users of the user equipment device audience. In a working mode, the system can process current user inputs to match a current user to one of the identified users of that user equipment device audience. Fuzzy logic and/or stochastic filtering may be used to improve development of the user characterizations, as well as matching of the current user to those developed characterizations. In this manner, targeting of assets can be implemented not only based on characteristics of a household but based on a current user within that household.

Abstract translation: 目标广告系统为用户设备设备（例如，有线网络中的数字机顶盒）的当前用户选择资产（例如，广告）。 系统可以首先在学习模式下操作以接收用户输入并且开发可以表征用户设备设备受众的多个用户的证据。 在工作模式下，系统可以处理当前用户输入以将当前用户与该用户设备设备受众的所识别用户之一相匹配。 模糊逻辑和/或随机过滤可以用于改进用户表征的开发，以及当前用户与那些开发的表征的匹配。 以这种方式，资产的目标不仅可以基于家庭的特征，而且还可以基于该家庭内的当前用户。