会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 5. 发明授权
    • Mixtures of Bayesian networks
    • 贝叶斯网络的混合
    • US06807537B1
    • 2004-10-19
    • US08985114
    • 1997-12-04
    • Bo ThiessonChristopher A. MeekDavid Maxwell ChickeringDavid Earl Heckerman
    • Bo ThiessonChristopher A. MeekDavid Maxwell ChickeringDavid Earl Heckerman
    • G06N302
    • G06K9/6296G06N5/025Y10S707/99945Y10S707/99948
    • One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
    • 本发明的一个方面是构建贝叶斯网络的混合物。 本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。 贝叶斯网络(MBN)的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络(HSBN)组成。 常见的外部隐藏变量与MBN相关联,但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数,并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。 在本发明的一种模式中,选择具有最高MBN分数的MBN用于执行推定。 在本发明的另一模式中,一些或所有MBN被保留为并行执行推论的MBN的集合,其输出根据相应的MBN分数加权,并且MBN收集输出是所有MBN的加权和 输出。 在本发明的一个应用中,可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。
    • 8. 发明授权
    • Offline counterfactual analysis
    • 离线反事实分析
    • US08606608B2
    • 2013-12-10
    • US12972417
    • 2010-12-17
    • Leon BottouDenis CharlesDavid Maxwell ChickeringPatrice Simard
    • Leon BottouDenis CharlesDavid Maxwell ChickeringPatrice Simard
    • G06Q10/00
    • G06Q30/0243
    • Counterfactual analysis can be performed “offline”, or “after the fact”, based on data collected during a trial in which random variations are applied to the output of the system whose parameters are to be the subject of the counterfactual analysis. A weighting factor can be derived and applied to data collected during the trial to emphasize that data obtained when the random variations most closely resembled the output that would be expected if counterfactual parameters were utilized to generate the output. If the counterfactual parameters being considered differ too much from the parameters under which the trial was conducted, the offline counterfactual analysis can estimate a direction and magnitude of the change of the system performance, as opposed to deriving a specific expected system performance value. In economic transactions, the random variations can be considered variations in the price paid by another party, thereby enabling derivation of their marginal cost.
    • 反事实分析可以基于在试验期间收集的数据“离线”或“事后”进行,其中随机变量应用于其参数作为反事实分析的对象的系统的输出。 可以导出加权因子并将其应用于在试验期间收集的数据,以强调当随机变量最接近地类似于如果使用反事实参数来产生输出时将被预期的输出获得的数据。 如果所考虑的反事实参数与进行试验的参数有太大差异,那么脱机反事实分析可以估计系统性能变化的方向和幅度,而不是推导具体的预期系统性能值。 在经济交易中,随机变化可以被认为是另一方支付的价格变动,从而能够推算其边际成本。