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    • 4. 发明申请
    • Dynamic Internet Advertising System
    • 动态互联网广告系统
    • US20160019606A1
    • 2016-01-21
    • US14870518
    • 2015-09-30
    • Shang Qing GuoJeffrey Owen KephartJonathan Lenchner
    • Shang Qing GuoJeffrey Owen KephartJonathan Lenchner
    • G06Q30/02
    • Methods and apparatus are provided for the dynamic placement, management and monitoring of Internet advertising. A provider of Internet content distributes the Internet content by embedding an advertisement placeholder in the Internet content; and provides the Internet content to an aggregator web site. The aggregator web site presents the Internet content to at least one end user with at least one advertisement in the advertisement placeholder. The advertisement placeholder is processed by a third party agent to automatically share revenue from the at least one advertisement with the provider of the Internet content and a provider of the aggregator web site. The advertisement placeholder can optionally be embedded in the Internet content using one or more templates. The third party agent also evaluates the content and at least one policy of multiple parties to identify at least one advertisement to present in the advertisement placeholder. The advertisement placeholder embodies a three party agreement between the provider of the Internet content, the provider of the aggregator web site and at least one advertiser.
    • 为互联网广告的动态放置,管理和监控提供了方法和设备。 互联网内容提供商通过在互联网内容中嵌入广告占位符来分发互联网内容; 并将互联网内容提供给聚合器网站。 聚合器网站将广告占位符中的至少一个广告的互联网内容呈现给至少一个终端用户。 广告占位符由第三方代理进行处理,以与互联网内容的提供者和聚合者网站的提供者自动分享来自至少一个广告的收入。 广告占位符可以可选地使用一个或多个模板嵌入到因特网内容中。 第三方代理还评估多方的内容和至少一个策略,以识别出在广告占位符中呈现的至少一个广告。 广告占位符体现了互联网内容提供商,聚合者网站提供商和至少一个广告客户之间的三方协议。
    • 5. 发明申请
    • Asset Identity Resolution Via Automatic Model Mapping Between Systems With Spatial Data
    • 资产身份解析通过空间数据系统之间的自动模型映射
    • US20130159351A1
    • 2013-06-20
    • US13325758
    • 2011-12-14
    • Hendrik F. HamannJeffrey Owen KephartJonathan LenchnerPeini LiuBo Yang
    • Hendrik F. HamannJeffrey Owen KephartJonathan LenchnerPeini LiuBo Yang
    • G06F17/30
    • G06Q10/087
    • Techniques for mapping between data models where objects represented in the data models include common physical objects or assets are provided. In one aspect, a method for mapping between data models, each of which describes a location of objects in a physical area includes the following steps. Common attributes are found in each of the data models. Location attributes are found among the common attributes in each of the data models, i.e., those attributes that describe the location of the objects in the physical area. The location attributes are used to identify a given one of the objects common to each of the data models, based on a placement of the given object by the data models at a same location (at a same time) in the physical area to establish a common identity of the object within the models. Attributes other than location attributes may then be mapped.
    • 提供数据模型之间的映射技术,其中数据模型中表示的对象包括公共物理对象或资产。 在一个方面,一种用于在数据模型之间映射的方法,每个数据模型描述物理区域中的对象的位置包括以下步骤。 在每个数据模型中都有公共属性。 在每个数据模型中的公共属性之间找到位置属性,即描述物理区域中的对象位置的那些属性。 位置属性用于基于在物理区域中的相同位置(同时)处的数据模型的给定对象的位置来识别每个数据模型共同的给定对象之一,以建立 模型中对象的共同身份。 然后可以映射除位置属性之外的属性。
    • 9. 发明授权
    • Method and apparatus for detecting a presence of a computer virus
    • 用于检测计算机病毒存在的方法和装置
    • US5907834A
    • 1999-05-25
    • US619866
    • 1996-03-18
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • Jeffrey Owen KephartGregory Bret SorkinGerald James TesauroSteven Richard White
    • G06F1/00G06F21/00G06F15/18G06F11/00
    • G06F21/564
    • A data string is a sequence of atomic units of data that represent information. In the context of computer data, examples of data strings include executable programs, data files, and boot records consisting of sequences of bytes, or text files consisting of sequences of bytes or characters. The invention solves the problem of automatically constructing a classifier of data strings, i.e., constructing a classifier which, given a string, determines which of two or more class labels should be assigned to it. From a set of (string, class-label) pairs, this invention provides an automated technique for extracting features of data strings that are relevant to the classification decision, and an automated technique for developing a classifier which uses those features to classify correctly the data strings in the original examples and, with high accuracy, classify correctly novel data strings not contained in the example set. The classifier is developed using "adaptive" or "learning" techniques from the domain of statistical regression and classification, such as, e.g., multi-layer neural networks. As an example, the technique can be applied to the task of distinguishing files or boot records that are infected by computer viruses from files or boot records that are not infected.
    • 数据串是表示信息的数据的原子单元的序列。 在计算机数据的上下文中,数据串的示例包括由字节序列组成的可执行程序,数据文件和引导记录,或由字节或字符序列组成的文本文件。 本发明解决了自动构建数据串分类器的问题,即,构建一个分类器,给定一个字符串,确定应该分配两个或多个类标签中的哪一个。 本发明从一组(串,类标签)对提供了一种用于提取与分类决定相关的数据串的特征的自动化技术,以及用于开发分类器的自动化技术,其使用这些特征来正确地分类数据 原始示例中的字符串,并且具有高精度,正确地分类示例集中未包含的新颖数据字符串。 分类器是使用“自适应”或“学习”技术从统计回归和分类领域开发的,例如多层神经网络。 例如,该技术可以应用于区分受计算机病毒感染的文件或引导记录的文件或未被感染的引导记录的任务。