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    Methods and apparatus to monitor network layer functionalities
    41.
    发明授权
    Methods and apparatus to monitor network layer functionalities 有权
    监测网络层功能的方法和装置

    公开(公告)号：US07944844B2

    公开(公告)日：2011-05-17

    申请号：US12343735

    申请日：2008-12-24

    申请人： Cheng Tien Ee ,  Lee M. Breslau ,  Kadangode K. Ramakrishnan

    发明人： Cheng Tien Ee ,  Lee M. Breslau ,  Kadangode K. Ramakrishnan

    IPC分类号： H04L12/26

    CPC分类号： H04L45/72 ,  H04L43/0864 ,  H04L43/10 ,  H04L43/50

    摘要： Example methods and apparatus to monitor network layer functionalities are disclosed. A disclosed example method includes receiving a first probe packet at an input of a first server, the first probe packet being received from a router, the first probe packet being generated and transmitted from a second server that is one-hop away from the first server in a network, determining if the first server is a final destination of the first probe packet, and if the first server is not the final destination of the first probe packet, generating a second probe packet and transmitting the second probe packet to the router for transmission toward the final destination.

    摘要翻译： 公开了用于监视网络层功能的示例性方法和装置。 所公开的示例性方法包括在第一服务器的输入端处接收第一探测分组，从路由器接收第一探测分组，从与第一服务器一跳的第二服务器生成并发送第一探测分组 在网络中，确定所述第一服务器是否是所述第一探测分组的最终目的地，并且如果所述第一服务器不是所述第一探测分组的最终目的地，则生成第二探测分组并将所述第二探测分组发送到所述路由器 传输到最终目的地。

    User-Powered Recommendation System
    43.
    发明申请
    User-Powered Recommendation System 有权
    用户推荐系统

    公开(公告)号：US20100138443A1

    公开(公告)日：2010-06-03

    申请号：US12616892

    申请日：2009-11-12

    申请人： Kadangode K. Ramakrishnan ,  Divesh Srivastava ,  Tae Won Cho ,  Yin Zhang

    发明人： Kadangode K. Ramakrishnan ,  Divesh Srivastava ,  Tae Won Cho ,  Yin Zhang

    IPC分类号： G06F17/30

    CPC分类号： G06N7/005 ,  G06F17/30038 ,  G06F17/30412 ,  G06F17/3097 ,  G11B27/105 ,  H04N21/4661 ,  H04N21/4668 ,  H04N21/4756

    摘要： Recommendation systems are widely used in Internet applications. In current recommendation systems, users only play a passive role and have limited control over the recommendation generation process. As a result, there is often considerable mismatch between the recommendations made by these systems and the actual user interests, which are fine-grained and constantly evolving. With a user-powered distributed recommendation architecture, individual users can flexibly define fine-grained communities of interest in a declarative fashion and obtain recommendations accurately tailored to their interests by aggregating opinions of users in such communities. By combining a progressive sampling technique with data perturbation methods, the recommendation system is both scalable and privacy-preserving.

    摘要翻译： 推荐系统广泛应用于互联网应用。 在目前的推荐系统中，用户只能发挥被动的作用，对推荐生成过程的控制有限。 因此，这些系统提出的建议和实际用户兴趣之间经常存在很大的不匹配，这些建议是细粒度和不断发展的。 通过用户分配的推荐体系结构，个人用户可以灵活地定义精细的社区，并以声明方式定义感兴趣的社区，通过汇总用户在这些社区的意见，获得准确定制的兴趣建议。 通过将逐行采样技术与数据扰动方法相结合，推荐系统既可扩展又保密。