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1. 发明授权

US08606608B2 Offline counterfactual analysis 有权
标题翻译：离线反事实分析
公开(公告)号：US08606608B2
公开(公告)日：2013-12-10
申请号：US12972417
申请日：2010-12-17
申请人： Leon Bottou , Denis Charles , David Maxwell Chickering , Patrice Simard
发明人： Leon Bottou , Denis Charles , David Maxwell Chickering , Patrice Simard
IPC分类号： G06Q10/00
CPC分类号： G06Q30/0243
摘要： 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.
摘要翻译：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。

2. 发明申请

US20120158488A1 OFFLINE COUNTERFACTUAL ANALYSIS 有权
标题翻译：离线反应分析
公开(公告)号：US20120158488A1
公开(公告)日：2012-06-21
申请号：US12972417
申请日：2010-12-17
申请人： Leon Bottou , Denis Charles , David Maxwell Chickering , Patrice Simard
发明人： Leon Bottou , Denis Charles , David Maxwell Chickering , Patrice Simard
IPC分类号： G06Q30/00 , G06F17/30
CPC分类号： G06Q30/0243
摘要： 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.
摘要翻译：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。

3. 发明授权

US07908328B1 Identification of email forwarders 有权
标题翻译：电子邮件转发器的识别
公开(公告)号：US07908328B1
公开(公告)日：2011-03-15
申请号：US11023293
申请日：2004-12-27
申请人： Geoffrey J Hulten , Anthony P. Penta , David Maxwell Chickering , Eliot C. Gillum , Gopalakrishnan Seshadrinathan , Jay T. Buckingham , Joshua T. Goodman , Paul S Rehfuss , Robert L. Rounthwaite , Ryan C Colvin
发明人： Geoffrey J Hulten , Anthony P. Penta , David Maxwell Chickering , Eliot C. Gillum , Gopalakrishnan Seshadrinathan , Jay T. Buckingham , Joshua T. Goodman , Paul S Rehfuss , Robert L. Rounthwaite , Ryan C Colvin
IPC分类号： G06F15/16
CPC分类号： H04L51/12
摘要： Identification of email forwarders is described. In an implementation, a method includes using heuristics to identify email forwarders for use in a reputation system for locating spammers. In another implementation, a method includes determining a likelihood that a particular Internet Protocol (IP) address corresponds to an email forwarder and processing email originating from the particular IP address based on the determined likelihood. In a further implementation, a method includes collecting heuristic data that describes characteristics of emails sent from one or more Internet Protocol (IP) addresses and constructing a model from the heuristic data for identifying whether at least one of the IP address is an email forwarder. In yet a further implementation, a method includes identifying that a particular Internet Protocol (IP) address likely corresponds to an email forwarder and processing email from the particular IP address based on an implied sender of the email.
摘要翻译：描述电子邮件转发器的识别。在一个实现中，一种方法包括使用启发式方法来识别在信誉系统中用于定位垃圾邮件发送者的电子邮件转发器。在另一实施方式中，一种方法包括确定特定因特网协议（IP）地址对应于电子邮件转发器的可能性，以及基于所确定的可能性处理来自该特定IP地址的电子邮件。在另一实现中，一种方法包括收集启发式数据，该启发式数据描述从一个或多个因特网协议（IP）地址发送的电子邮件的特征，并根据启发式数据构建模型，用于识别IP地址中的至少一个是电子邮件转发器。在又一个实现中，一种方法包括识别特定的因特网协议（IP）地址可能对应于电子邮件转发器，并且基于电子邮件的隐含发送者从特定IP地址处理电子邮件。

4. 发明授权

US07660705B1 Bayesian approach for learning regression decision graph models and regression models for time series analysis 有权
标题翻译：用于学习回归决策图模型的贝叶斯方法和时间序列分析的回归模型
公开(公告)号：US07660705B1
公开(公告)日：2010-02-09
申请号：US10102116
申请日：2002-03-19
申请人： Christopher A. Meek , David E. Heckerman , Robert L. Rounthwaite , David Maxwell Chickering , Bo Thiesson
发明人： Christopher A. Meek , David E. Heckerman , Robert L. Rounthwaite , David Maxwell Chickering , Bo Thiesson
IPC分类号： G06F17/10
CPC分类号： G06K9/6297
摘要： Methods and systems are disclosed for learning a regression decision graph model using a Bayesian model selection approach. In a disclosed aspect, the model structure and/or model parameters can be learned using a greedy search algorithm applied to grow the model so long as the model improves. This approach enables construction of a decision graph having a model structure that includes a plurality of leaves, at least one of which includes a non-trivial linear regression. The resulting model thus can be employed for forecasting, such as for time series data, which can include single or multi-step forecasting.
摘要翻译：公开了使用贝叶斯模型选择方法学习回归决策图模型的方法和系统。在公开的方面，只要模型改进，可以使用应用于增长模型的贪心搜索算法来学习模型结构和/或模型参数。该方法能够构建具有包括多个叶子的模型结构的决策图，其中至少一个包括非平凡的线性回归。因此，所得到的模型可以用于预测，例如用于时间序列数据，其可以包括单步或多步预测。

5. 发明授权

US06831663B2 System and process for automatically explaining probabilistic predictions 有权
标题翻译：自动解释概率预测的系统和过程
公开(公告)号：US06831663B2
公开(公告)日：2004-12-14
申请号：US09681709
申请日：2001-05-24
申请人： David Maxwell Chickering , David E. Heckerman , Robert Rounthwaite
发明人： David Maxwell Chickering , David E. Heckerman , Robert Rounthwaite
IPC分类号： G09G500
CPC分类号： G06Q30/02 , G06Q10/02 , Y10S707/99932 , Y10S707/99933 , Y10S707/99934 , Y10S707/99943
摘要： The system and method of the present invention automatically assigns “scores” to the predictor/variable value pairs of a conventional probabilistic model to measure the relative impact or influence of particular elements of a set of topics, items, products, etc. in making specific predictions using the probabilistic model. In particular, these scores measure the relative impact, either positive or negative, that the value of each individual predictor variable has on the posterior distribution of the target topic, item, product, etc., for which a probability is being determined. These scores are useful for understanding why each prediction is make, and how much impact each predictor has on the prediction. Consequently, such scores are useful for explaining why a particular prediction or recommendation was made.
摘要翻译：本发明的系统和方法自动地将“分数”分配给常规概率模型的预测值/变量值对，以测量一组主题，项目，产品等的特定元素对制作具体的相对影响或影响使用概率模型的预测。特别地，这些分数测量相对影响，无论是正面还是负面，每个单个预测变量的值对于其中确定概率的目标主题，项目，产品等的后验分布。这些分数对于了解每个预测的原因以及每个预测者对预测的影响有多大。因此，这些分数对于解释为什么进行特定的预测或建议是有用的。

6. 发明授权

US06336108B1 Speech recognition with mixtures of bayesian networks 有权
标题翻译：语音识别与贝叶斯网络的混合
公开(公告)号：US06336108B1
公开(公告)日：2002-01-01
申请号：US09220197
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman , Fileno A. Alleva , Mei-Yuh Hwang
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman , Fileno A. Alleva , Mei-Yuh Hwang
IPC分类号： G06F1518
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： The invention performs speech recognition using an array of mixtures of Bayesian networks. 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 models the world under the hypothesis that the common external hidden variable is in a corresponding one of those states. In accordance with the invention, the MBNs encode the probabilities of observing the sets of acoustic observations given the utterance of a respective one of said parts of speech. Each of the HSBNs encodes the probabilities of observing the sets of acoustic observations given the utterance of a respective one of the parts of speech and given a hidden common variable being in a particular state. Each HSBN has nodes corresponding to the elements of the acoustic observations. These nodes store probability parameters corresponding to the probabilities with causal links representing dependencies between ones of said nodes.
摘要翻译：本发明使用贝叶斯网络混合的阵列来执行语音识别。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的数量对应于共同外部隐藏变量的状态数，并且每个HSBN在假设下共同的外部隐藏变量处于相应的一个状态的假设下对世界进行建模。根据本发明，MBN编码了考虑到所述话音部分中的相应一个的话语来观察声学观测组的概率。每个HSBN编码观察给定语音相应的一个语音的发音并给出隐藏的公共变量处于特定状态的声学观察组的概率。每个HSBN具有对应于声学观测元素的节点。这些节点存储对应于概率的概率参数，其中因果链接表示所述节点之间的依赖关系。

7. 发明授权

US07953738B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US07953738B2
公开(公告)日：2011-05-31
申请号：US10955585
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06F17/30
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

8. 发明授权

US07389201B2 System and process for automatically providing fast recommendations using local probability distributions 有权
标题翻译：使用本地概率分布自动提供快速建议的系统和过程
公开(公告)号：US07389201B2
公开(公告)日：2008-06-17
申请号：US09681742
申请日：2001-05-30
申请人： David Maxwell Chickering , David E. Heckerman , Robert Rounthwaite
发明人： David Maxwell Chickering , David E. Heckerman , Robert Rounthwaite
IPC分类号： G06F19/00
CPC分类号： G06Q10/04 , G06Q30/02 , G06Q40/025
摘要： The system and method of the present invention automatically extracts the top k recommendations of objects, such as topics, items, products, books, movies, food, drinks, etc., from a local probabilistic recommendation system. Unlike prior systems, the present invention accomplishes the extraction of the top k recommendations of objects without examining a probability for every object that can be recommended. Further, the system and method of the present invention is capable of being implemented using probabilistic recommendation systems based on any conventional type of probabilistic distribution or machine learning technique, including, for example, decision trees and Bayesian networks.
摘要翻译：本发明的系统和方法从本地概率推荐系统自动提取诸如主题，项目，产品，书籍，电影，食品，饮料等的物体的顶部k建议。与现有系统不同，本发明完成了对对象的顶部k建议的提取，而不检查可推荐的每个对象的概率。此外，本发明的系统和方法能够使用基于任何常规类型的概率分布或机器学习技术的概率推荐系统来实现，包括例如决策树和贝叶斯网络。

9. 发明授权

US07324981B2 System and method of employing efficient operators for Bayesian network search 有权
标题翻译：贝叶斯网络搜索采用有效运算符的系统和方法
公开(公告)号：US07324981B2
公开(公告)日：2008-01-29
申请号：US10147620
申请日：2002-05-16
申请人： David Maxwell Chickering
发明人： David Maxwell Chickering
IPC分类号： G06N5/00
CPC分类号： G06N7/005 , Y10S707/99933 , Y10S707/99935
摘要： Methods and systems are disclosed for learning Bayesian networks. The approach is based on specifying a search space that enables searching over equivalence classes of the Bayesian network. A set of one or more operators are applied to a representation of the equivalence class. A suitable search algorithm searches in the search space by scoring the operators locally with a decomposable scoring criteria. To facilitate application of the operators and associated scoring, validity tests can be performed to determine whether a given operator is valid relative to the current state representation.
摘要翻译：公开了用于学习贝叶斯网络的方法和系统。该方法基于指定搜索空间，其能够搜索贝叶斯网络的等价类。一组一个或多个运算符被应用于等价类的表示。合适的搜索算法在搜索空间中通过使用可分解评分标准对本地运算符进行本地评分来搜索。为了便于运营商的应用和相关的评分，可以执行有效性测试以确定给定运算符是否相对于当前状态表示是有效的。

10. 发明授权

US07158959B1 Automated web-based targeted advertising with quotas 有权
标题翻译：自动化基于网络的定向广告配额
公开(公告)号：US07158959B1
公开(公告)日：2007-01-02
申请号：US11047276
申请日：2005-01-31
申请人： David Maxwell Chickering , David E. Heckerman
发明人： David Maxwell Chickering , David E. Heckerman
IPC分类号： G06N706/045
CPC分类号： G06Q30/00 , G06Q30/0269 , G06Q30/0273 , G06Q30/0277
摘要： The invention provides systems and methods that can be used for targeted advertising. The system determines where to present impressions, such as advertisements, to maximize an expected utility subject to one or more constraints, which can include quotas and minimum utilities for groups of one or more impression. The traditional measure of utility in web-based advertising is click-though rates, but the present invention provides a broader definition of utility, including measures of sales, profits, or brand awareness, for example. This broader definition permits advertisements to be allocated more in accordance with the actual interests of advertisers.
摘要翻译：本发明提供了可用于有针对性的广告的系统和方法。该系统确定在何处呈现印象，例如广告，以最大限度地利用一个或多个约束的期望效用，其中可以包括一个或多个印象的组的配额和最小实用程序。基于网络广告的传统效用测度是点击率，但本发明提供了更广泛的效用定义，例如销售，利润或品牌知名度等。这种更广泛的定义允许根据广告商的实际利益更多地分配广告。

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