Invention Grant
US08676909B2 Method, system and architecture for delivering messages in a network to automatically increase a signal-to-noise ratio of user interests 有权
用于在网络中传递消息以自动提高用户兴趣的信噪比的方法,系统和架构

  • Patent Title: Method, system and architecture for delivering messages in a network to automatically increase a signal-to-noise ratio of user interests
  • Patent Title (中): 用于在网络中传递消息以自动提高用户兴趣的信噪比的方法,系统和架构
  • Application No.: US13377610
    Application Date: 2010-06-15
  • Publication No.: US08676909B2
    Publication Date: 2014-03-18
  • Inventor: Paul GuyotJean-Charles Campagne
  • Applicant: Paul GuyotJean-Charles Campagne
  • Applicant Address: FR Paris
  • Assignee: Semiocast
  • Current Assignee: Semiocast
  • Current Assignee Address: FR Paris
  • Priority: EP09008171 20090622
  • International Application: PCT/EP2010/003676 WO 20100615
  • International Announcement: WO2010/149312 WO 20101229
  • Main IPC: G06F15/16
  • IPC: G06F15/16
Method, system and architecture for delivering messages in a network to automatically increase a signal-to-noise ratio of user interests
Abstract:
The present invention pertains to a method for delivering messages in a social network to increase a signal-to-noise ratio for the recipients of messages, characterized in that a process mechanism comprises of a diffusion process and a selection process combined through an adaptive process, in which: the diffusion process dispatches each message through dynamic routing graphs defined between the sender user and a set of potentially interested recipient users; the selection process locally filters the messages that are transmitted from sender users and received by potentially interested recipient users, according to the result of the application of a selection function on the metadata values constituting a message profile extracted from each transmitted message and weighted feature values constituting a user profile of the recipient to establish an estimate of interest for the user regarding each message, and the adaptive process continuously adjusts processing functions to adapt the graphs structure according to the user profiles dynamically updated by message metadata.
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