专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

91. 发明授权

US07219148B2 Feedback loop for spam prevention 有权
标题翻译：防止垃圾邮件的反馈回路
公开(公告)号：US07219148B2
公开(公告)日：2007-05-15
申请号：US10378463
申请日：2003-03-03
申请人： Robert L. Rounthwaite , Joshua T. Goodman , David E. Heckerman , John D. Mehr , Nathan D. Howell , Micah C. Rupersburg , Dean A. Slawson
发明人： Robert L. Rounthwaite , Joshua T. Goodman , David E. Heckerman , John D. Mehr , Nathan D. Howell , Micah C. Rupersburg , Dean A. Slawson
IPC分类号： G06F15/173
CPC分类号： H04L51/12 , G06Q10/107
摘要： The subject invention provides for a feedback loop system and method that facilitate classifying items in connection with spam prevention in server and/or client-based architectures. The invention makes uses of a machine-learning approach as applied to spam filters, and in particular, randomly samples incoming email messages so that examples of both legitimate and junk/spam mail are obtained to generate sets of training data. Users which are identified as spam-fighters are asked to vote on whether a selection of their incoming email messages is individually either legitimate mail or junk mail. A database stores the properties for each mail and voting transaction such as user information, message properties and content summary, and polling results for each message to generate training data for machine learning systems. The machine learning systems facilitate creating improved spam filter(s) that are trained to recognize both legitimate mail and spam mail and to distinguish between them.
摘要翻译：本发明提供了一种反馈循环系统和方法，其有助于在服务器和/或基于客户端的体系结构中与垃圾邮件防止相关联的项目进行分类。本发明将机器学习方法应用于垃圾邮件过滤器，特别是随机抽取传入的电子邮件消息，以便获得合法和垃圾/垃圾邮件的示例以生成训练数据集。被要求被识别为垃圾邮件战士的用户被要求投票选择他们的收到的电子邮件的选择是单独的合法邮件还是垃圾邮件。数据库存储每个邮件和投票交易的属性，例如用户信息，消息属性和内容摘要，以及每个消息的轮询结果，以生成机器学习系统的训练数据。机器学习系统便于创建改进的垃圾邮件过滤器，该过滤器被训练以识别合法邮件和垃圾邮件并区分它们。

92. 发明授权

US07133811B2 Staged mixture modeling 有权
标题翻译：分阶段混合建模
公开(公告)号：US07133811B2
公开(公告)日：2006-11-07
申请号：US10270914
申请日：2002-10-15
申请人： Bo Thiesson , Christopher A. Meek , David E. Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David E. Heckerman
IPC分类号： G06F17/10
CPC分类号： G06K9/6226 , G06F17/18 , Y10S707/99935 , Y10S707/99936 , Y10S707/99942
摘要： A system and method for generating staged mixture model(s) is provided. The staged mixture model includes a plurality of mixture components each having an associated mixture weight, and, an added mixture component having an initial structure, parameters and associated mixture weight. The added mixture component is modified based, at least in part, upon a case that is undesirably addressed by the plurality of mixture components using a structural expectation maximization (SEM) algorithm to modify at the structure, parameters and/or associated mixture weight of the added mixture component.The staged mixture model employs a data-driven staged mixture modeling technique, for example, for building density, regression, and classification model(s). The basic approach is to add mixture component(s) (e.g., sequentially) to the staged mixture model using an SEM algorithm.
摘要翻译：提供了一种用于生成分段混合模型的系统和方法。分级混合物模型包括各自具有相关混合物重量的多种混合物组分，以及具有初始结构，参数和相关混合物重量的添加的混合物组分。至少部分地，添加的混合物组分基于使用结构期望最大化（SEM）算法不期望地由多个混合物组分解决的情况进行修饰，以在结构，参数和/或相关联的混合物重量加入的混合物组分。分级混合模型采用数据驱动的分段混合建模技术，例如建筑密度，回归和分类模型。基本方法是使用SEM算法将混合物组分（例如，顺序地）添加到分级混合物模型中。

93. 发明授权

US07065534B2 Anomaly detection in data perspectives 失效
标题翻译：数据透视异常检测
公开(公告)号：US07065534B2
公开(公告)日：2006-06-20
申请号：US10874956
申请日：2004-06-23
申请人： Allan Folting , Bo Thiesson , David E. Heckerman , David M. Chickering , Eric Barber Vigesaa
发明人： Allan Folting , Bo Thiesson , David E. Heckerman , David M. Chickering , Eric Barber Vigesaa
IPC分类号： G06F7/00 , G06F17/00
CPC分类号： G06F17/30592 , G06N7/00 , Y10S707/957 , Y10S707/958 , Y10S707/99943
摘要： The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a “data tube” from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot tables and/or OLAP cubes. It determines if data substantially deviates from a predicted value established by a curve fitting process such as, for example, a piece-wise linear function applied to the data tube. A threshold value can also be employed by the present invention to facilitate in determining a degree of deviation necessary before a data value is considered anomalous. The threshold value can be supplied dynamically and/or statically by a system and/or a user via a user interface. Additionally, the present invention provides an indication to a user of the type and location of a detected anomaly from a top level data perspective.
摘要翻译：本发明利用曲线拟合数据技术从数据角度提供“数据管”中的数据异常的自动检测，从而允许例如检测诸如屏幕上的数据异常，向下钻取和钻取数据异常的数据异常例如，枢轴表和/或OLAP多维数据集。它确定数据是否基本上偏离由曲线拟合处理（例如应用于数据管的分段线性函数）所建立的预测值。本发明也可以采用阈值，以便在确定数据值被认为是异常之前确定所需的偏差程度。阈值可以由系统和/或用户经由用户界面动态地和/或静态地提供。另外，本发明从顶级数据的角度向用户提供了检测到的异常的类型和位置的指示。

94. 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。

95. 发明授权

US06771289B1 Cluster-based visualization of user traffic on an internet site 失效
标题翻译：互联网网站上用户流量的基于群集的可视化
公开(公告)号：US06771289B1
公开(公告)日：2004-08-03
申请号：US09517462
申请日：2000-03-02
申请人： Igor Cadez , David E. Heckerman , Christopher A. Meek , Steven J. White
发明人： Igor Cadez , David E. Heckerman , Christopher A. Meek , Steven J. White
IPC分类号： G06F314
CPC分类号： H04L67/22 , H04L41/0893 , H04L41/22 , Y10S707/99937
摘要： Visualizing Internet web traffic is disclosed. In one embodiment, a number of windows are displayed, corresponding to a number of clusters into which users have been partitioned based on similar web browsing behavior. The windows are ordered from the cluster having the greatest number of users to the cluster having the least number of users. Each window has one or more rows, where each row corresponds to a user within the cluster. Each row has an ordered number of visible units, such as blocks, where each block corresponds to a web page visited by the user. The blocks can be color coded by the type of web page they represent. In one embodiment, the corresponding cluster models for the clusters are alternatively displayed in the windows.
摘要翻译：透露互联网流量的可视化。在一个实施例中，根据类似的网页浏览行为，显示对应于用户已被划分到的群集的数量的多个窗口。 Windows从具有最多用户数量的群集排队到具有最少用户数量的群集。每个窗口都有一行或多行，其中每行对应于群集内的用户。每行都有一个有序数量的可见单元，例如块，其中每个块对应于用户访问的网页。这些块可以通过它们所代表的网页的类型进行颜色编码。在一个实施例中，用于集群的对应的集群模型交替地显示在窗口中。

96. 发明授权

US06665653B1 Noise reduction for a cluster-based approach for targeted item delivery with inventory management 有权
标题翻译：基于群集的方法进行降噪，用于通过库存管理进行目标物品交付
公开(公告)号：US06665653B1
公开(公告)日：2003-12-16
申请号：US09565583
申请日：2000-05-04
申请人： David E. Heckerman , D. Maxwell Chickering
发明人： David E. Heckerman , D. Maxwell Chickering
IPC分类号： G06N504
CPC分类号： G06Q30/02
摘要： Reduction of noise within a cluster-based approach for item (such as ad) allocation, such as by using a linear program, is described. In one embodiment, probabilities are discretized into a predetermined number of groups, where the mean for the group that a particular probability has been discretized into is substituted for the particular probability when the items are being allocated. In another embodiment, the probabilities are decreased by a power function of the variances for them. In a third embodiment, allocation of items to clusters is not changed unless the sample sizes used to determine the corresponding probabilities for those ads is greater than a threshold. In a fourth embodiment, after allocation is performed a first time, a predetermined number of item are removed, and reallocation is performed.
摘要翻译：描述了基于群集的方法中的项目（例如广告）分配（例如通过使用线性程序）来减少噪声。在一个实施例中，将概率离散为预定数量的组，其中特定概率已被离散化的组的均值代替项目被分配时的特定概率。在另一个实施例中，通过它们的方差的幂函数来降低概率。在第三实施例中，除了用于确定这些广告的相应概率的样本大小大于阈值之外，项目到群集的分配也不会改变。在第四实施例中，在首次执行分配之后，去除预定数量的项目，并且执行重新分配。

97. 发明授权

US06519599B1 Visualization of high-dimensional data 有权
标题翻译：高维数据的可视化
公开(公告)号：US06519599B1
公开(公告)日：2003-02-11
申请号：US09517138
申请日：2000-03-02
申请人： D. Maxwell Chickering , David E. Heckerman , Christopher A. Meek , Robert L. Rounthwaite , Amir Netz , Thierry D'Hers
发明人： D. Maxwell Chickering , David E. Heckerman , Christopher A. Meek , Robert L. Rounthwaite , Amir Netz , Thierry D'Hers
IPC分类号： G06F1730
CPC分类号： G06F17/30994 , Y10S707/99945
摘要： Visualization of high-dimensional data sets is disclosed, particularly the display of a network model for a data set. The network, such as a dependency or a Bayesian network, has a number of nodes having dependencies thereamong. The network can be displayed items and connections, corresponding to nodes and dependencies, respectively. Selection of a particular item in one embodiment results in the display of the local distribution associated with the node for the item. In one embodiment, only a predetermined number of the items are shown, such as only the items representing the most popular nodes. Furthermore, in one embodiment, in response to receiving a user input, a sub-set of the connections is displayed, proportional to the user input. In another embodiment, a particular item is displayed in an emphasized manner, and the particular connections representing dependencies including the node represented by the particular item, as well as the items representing nodes also in these dependencies, are also displayed in the emphasized manner. Furthermore, in one embodiment, only an indicated sub-set of the items is displayed.
摘要翻译：公开了高维数据集的可视化，特别是显示数据集的网络模型。诸如依赖关系或贝叶斯网络的网络具有多个具有依赖关系的节点。网络可以分别显示对应于节点和依赖关系的项目和连接。在一个实施例中，特定项目的选择导致与项目的节点相关联的本地分布的显示。在一个实施例中，仅显示预定数量的项目，诸如仅表示最受欢迎节点的项目。此外，在一个实施例中，响应于接收到用户输入，显示与用户输入成比例的连接的子集。在另一个实施例中，以强调方式显示特定项目，并且还以强调的方式显示表示依赖性的特定连接，包括由特定项目表示的节点以及表示节点的项目也在这些依赖关系中。此外，在一个实施例中，仅显示所指示的项目子集。

98. 发明授权

US5802256A Generating improved belief networks 失效
公开(公告)号：US5802256A
公开(公告)日：1998-09-01
申请号：US862564
申请日：1997-05-23
申请人： David E. Heckerman , Dan Geiger , David M. Chickering
发明人： David E. Heckerman , Dan Geiger , David M. Chickering
IPC分类号： G06N5/02 , G06F15/18
CPC分类号： G06N5/022
摘要： An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator provides for the use of continuous variables in the generated belief network and missing data in the empirical data.

99. 发明授权

US5696884A Method for assisting in rendering a decision using improved belief networks 失效
标题翻译：使用改进的信念网络协助作出决定的方法
公开(公告)号：US5696884A
公开(公告)日：1997-12-09
申请号：US739201
申请日：1996-10-30
申请人： David E. Heckerman , Dan Geiger , David M. Chickering
发明人： David E. Heckerman , Dan Geiger , David M. Chickering
IPC分类号： G06N5/02 , G06F15/18
CPC分类号： G06N5/022
摘要： An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator of the preferred embodiment provides for the use of continuous variables in the generated belief network and missing data in the empirical data.
摘要翻译：提供了一种改进的信任网络生成器。使用从专家领域的专家知识获取的专家知识和反映在专家的给定领域中作出的观察的经验数据产生信念网络。除了利用专家知识和经验数据之外，优选实施例的信念网络生成器还提供了所生成的信念网络中的连续变量的使用以及经验数据中的丢失数据。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式