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1. 发明申请

US20090089161A1 INTEGRATING ENCAPSULATED ADVERTISEMENT CONTROLS 审中-公开
标题翻译：集成广告控制
公开(公告)号：US20090089161A1
公开(公告)日：2009-04-02
申请号：US11864340
申请日：2007-09-28
申请人： MAHBUBUL ALAM ALI , PRASANTH PULAVARTHI
发明人： MAHBUBUL ALAM ALI , PRASANTH PULAVARTHI
IPC分类号： G06Q30/00
CPC分类号： G06Q30/0264 , G06Q30/02
摘要： Computer-readable media, systems, and methods for integrating advertisements using encapsulated advertisement controls are described. In embodiments, one or more embedding instructions are received for embedding one or more encapsulated advertisement controls within an application, the one or more encapsulated advertisement controls including logic for handling of one or more advertisements and presentation of the advertisements to a user of the application. Further, in embodiments, one or more configuration instructions are received for configuring the one or more encapsulated advertisement controls. Still further, in embodiments, one or more advertisements are presented to a user of the application in accordance with the one or more advertisement presentation parameters.
摘要翻译：描述了使用封装的广告控件来集成广告的计算机可读介质，系统和方法。在实施例中，接收一个或多个嵌入指令以在应用程序内嵌入一个或多个封装的广告控件，所述一个或多个封装的广告控件包括用于处理一个或多个广告的逻辑以及向应用的用户呈现广告。此外，在实施例中，接收一个或多个配置指令以配置一个或多个封装的广告控件。此外，在实施例中，根据一个或多个广告呈现参数将一个或多个广告呈现给应用的用户。

2. 发明授权

US09135561B2 Inferring procedural knowledge from data sources 有权
标题翻译：从数据源中推断程序知识
公开(公告)号：US09135561B2
公开(公告)日：2015-09-15
申请号：US13291126
申请日：2011-11-08
申请人： Viswanath Vadlamani , Arungunram Surendran , Prasanth Pulavarthi , Phani Vaddadi , Munirathnam Srikanth , Tarek Najm
发明人： Viswanath Vadlamani , Arungunram Surendran , Prasanth Pulavarthi , Phani Vaddadi , Munirathnam Srikanth , Tarek Najm
IPC分类号： G06F15/18 , G06N5/04 , G06N5/02 , G06N99/00
CPC分类号： G06N5/022 , G06N5/04 , G06N99/005
摘要： A procedural inference system is described herein that infers procedural knowledge from various data sources to help a user complete one or more tasks for which the data sources provide information. The system understands users' queries, identifies a task at hand, provides recommendations on the steps to take and the agents to use based on a knowledge base of tasks and agents, and provides the fabric to determine which different agents can work together to help the user accomplish a task. Tasks can be started on one device and completed on another seamlessly. Users are able to finish complex, multi-step tasks efficiently, without trial and error or data reentry. Thus, the procedural inference system provides a generalized framework that helps users to complete tasks using already available data and does not ask each data provider to invest in infrastructure to build dedicated task information systems.
摘要翻译：本文描述了一种程序性推理系统，其推导来自各种数据源的程序性知识，以帮助用户完成数据源为其提供信息的一个或多个任务。系统了解用户的查询，识别手头的任务，根据任务和代理的知识库提供有关采取的步骤和代理使用的建议，并提供结构以确定哪些不同的代理可以协同工作用户完成任务。任务可以在一个设备上启动，另一个无缝完成。用户能够有效地完成复杂的多步骤任务，无需进行试错和数据重入。因此，程序推理系统提供了一个通用框架，可帮助用户使用已有的数据完成任务，并且不要求每个数据提供商投资于基础架构来构建专用的任务信息系统。

3. 发明申请

US20090006177A1 PROVIDING ADS TO UNCONNECTED CLIENT DEVICES 审中-公开
标题翻译：向不连续的客户端设备提供ADS
公开(公告)号：US20090006177A1
公开(公告)日：2009-01-01
申请号：US11770409
申请日：2007-06-28
申请人： John A. BEAVER , Brian E. TSCHUMPER , Prasanth PULAVARTHI , Wenjun QIU
发明人： John A. BEAVER , Brian E. TSCHUMPER , Prasanth PULAVARTHI , Wenjun QIU
IPC分类号： G06F19/00
CPC分类号： G06Q30/02 , G06Q30/0263 , Y10T70/5146
摘要： Techniques are disclosed, among other things, that provide ads to requesting applications while the client device is not connected to a communication network. An offline advertisement engine is provided for storing business rules for each of a plurality of corresponding stored advertisements, wherein the business rules and advertisements are stored locally on the client device. An offline advertisement media manager is also provided for storing creatives related to the stored advertisements, wherein the creatives are also stored locally on the client device. Moreover, an advertisement center client is disclosed for providing advertisements and creatives associated with the advertisement to an application in response to a request for the advertisements.
摘要翻译：公开了在客户端设备未连接到通信网络时提供广告以请求应用的技术。提供了一种离线广告引擎，用于存储多个相应存储的广告中的每一个的业务规则，其中业务规则和广告本地存储在客户端设备上。还提供离线广告媒体管理器用于存储与所存储的广告相关的广告，其中所述广告素材也本地存储在所述客户端设备上。此外，公开了一种广告中心客户端，用于响应于对广告的请求向应用提供与广告相关联的广告和广告。

4. 发明申请

US20130117204A1 INFERRING PROCEDURAL KNOWLEDGE FROM DATA SOURCES 有权
标题翻译：从数据来源传播程序知识
公开(公告)号：US20130117204A1
公开(公告)日：2013-05-09
申请号：US13291126
申请日：2011-11-08
申请人： Viswanath Vadlamani , Arungunram Surendran , Prasanth Pulavarthi , Phani Vaddadi , Munirathnam Srikanth , Tarek Najm
发明人： Viswanath Vadlamani , Arungunram Surendran , Prasanth Pulavarthi , Phani Vaddadi , Munirathnam Srikanth , Tarek Najm
IPC分类号： G06F15/18 , G06N5/04
CPC分类号： G06N5/022 , G06N5/04 , G06N99/005
摘要： A procedural inference system is described herein that infers procedural knowledge from various data sources to help a user complete one or more tasks for which the data sources provide information. The system understands users' queries, identifies a task at hand, provides recommendations on the steps to take and the agents to use based on a knowledge base of tasks and agents, and provides the fabric to determine which different agents can work together to help the user accomplish a task. Tasks can be started on one device and completed on another seamlessly. Users are able to finish complex, multi-step tasks efficiently, without trial and error or data reentry. Thus, the procedural inference system provides a generalized framework that helps users to complete tasks using already available data and does not ask each data provider to invest in infrastructure to build dedicated task information systems.
摘要翻译：本文描述了一种程序性推理系统，其推导来自各种数据源的程序性知识，以帮助用户完成数据源为其提供信息的一个或多个任务。系统了解用户的查询，识别手头的任务，根据任务和代理的知识库提供有关采取的步骤和代理使用的建议，并提供结构以确定哪些不同的代理可以协同工作用户完成任务。任务可以在一个设备上启动，另一个无缝完成。用户能够有效地完成复杂的多步骤任务，无需进行试错和数据重入。因此，程序推理系统提供了一个通用框架，可帮助用户使用已有的数据完成任务，并且不要求每个数据提供商投资于基础架构来构建专用的任务信息系统。

5. 发明授权

US07593906B2 Bayesian probability accuracy improvements for web traffic predictions 有权
标题翻译：网络流量预测的贝叶斯概率精度提高
公开(公告)号：US07593906B2
公开(公告)日：2009-09-22
申请号：US11461030
申请日：2006-07-31
申请人： David M. Chickering , Ashis K. Roy , Prasanth Pulavarthi
发明人： David M. Chickering , Ashis K. Roy , Prasanth Pulavarthi
IPC分类号： G06N7/00
CPC分类号： G06N7/005 , G06Q30/0246 , H04L41/08 , H04L41/147 , H04L41/16
摘要： Enhancements to Bayesian prediction models for network location traffic provide increased accuracy in web traffic predictions. The enhancements include implementing user advertising target queries to determine preferred edges of a Bayesian model, employing hierarchical data structures to cleanse training data for a Bayesian model, and/or augmenting existing data with new training data to enhance a previously constructed Bayesian model. Preferred edge enhancements for the Bayesian model utilize target attribute derived preferred edges and/or explicitly specified preferred edges. Training data is cleansed utilizing tag hierarchies that can employ parent-child relationships, ancestor relationships, and/or network location specific parameters. New training data can also be employed to adjust probabilities in a previously constructed Bayesian model. The new training data can be weighted differently than data represented by the previously constructed Bayesian model.
摘要翻译：对网络位置流量的贝叶斯预测模型的增强提高了网络流量预测的准确性。增强包括实现用户广告目标查询以确定贝叶斯模型的优选边缘，采用分层数据结构来清除贝叶斯模型的训练数据，和/或用新的训练数据增强现有数据以增强先前构造的贝叶斯模型。贝叶斯模型的优选边缘增强使用目标属性导出的优选边缘和/或明确指定的优选边缘。使用可以使用父子关系，祖先关系和/或网络位置特定参数的标签层次来清理训练数据。也可以使用新的训练数据来调整先前构造的贝叶斯模型中的概率。新的训练数据可以与先前构造的贝叶斯模型所代表的数据不同。

6. 发明申请

US20080027890A1 BAYESIAN PROBABILITY ACCURACY IMPROVEMENTS FOR WEB TRAFFIC PREDICTIONS 有权
标题翻译：网络交通预测的贝叶斯可靠性准确性改进
公开(公告)号：US20080027890A1
公开(公告)日：2008-01-31
申请号：US11461030
申请日：2006-07-31
申请人： David M. Chickering , Ashis K. Roy , Prasanth Pulavarthi
发明人： David M. Chickering , Ashis K. Roy , Prasanth Pulavarthi
IPC分类号： G06N7/02
CPC分类号： G06N7/005 , G06Q30/0246 , H04L41/08 , H04L41/147 , H04L41/16
摘要： Enhancements to Bayesian prediction models for network location traffic provide increased accuracy in web traffic predictions. The enhancements include implementing user advertising target queries to determine preferred edges of a Bayesian model, employing hierarchical data structures to cleanse training data for a Bayesian model, and/or augmenting existing data with new training data to enhance a previously constructed Bayesian model. Preferred edge enhancements for the Bayesian model utilize target attribute derived preferred edges and/or explicitly specified preferred edges. Training data is cleansed utilizing tag hierarchies that can employ parent-child relationships, ancestor relationships, and/or network location specific parameters. New training data can also be employed to adjust probabilities in a previously constructed Bayesian model. The new training data can be weighted differently than data represented by the previously constructed Bayesian model.
摘要翻译：对网络位置流量的贝叶斯预测模型的增强提高了网络流量预测的准确性。增强包括实现用户广告目标查询以确定贝叶斯模型的优选边缘，采用分层数据结构来清除贝叶斯模型的训练数据，和/或用新的训练数据增强现有数据以增强先前构造的贝叶斯模型。贝叶斯模型的优选边缘增强使用目标属性导出的优选边缘和/或明确指定的优选边缘。使用可以使用父子关系，祖先关系和/或网络位置特定参数的标签层次来清理训练数据。也可以使用新的训练数据来调整先前构造的贝叶斯模型中的概率。新的训练数据可以与先前构造的贝叶斯模型所代表的数据不同。

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