公开(公告)号：US08626136B2

公开(公告)日：2014-01-07

申请号：US11427755

申请日：2006-06-29

Applicant: Raymond E. Ozzie ,  Eric J. Horvitz ,  William H. Gates, III ,  Joshua T. Goodman ,  Susan T. Dumais ,  Gary W. Flake ,  Trenholme J. Griffin ,  Xuedong D. Huang ,  Oliver Hurst-Hiller ,  Christopher A Meek

Inventor： Raymond E. Ozzie ,  Eric J. Horvitz ,  William H. Gates, III ,  Joshua T. Goodman ,  Susan T. Dumais ,  Gary W. Flake ,  Trenholme J. Griffin ,  Xuedong D. Huang ,  Oliver Hurst-Hiller ,  Christopher A Meek

IPC: H04M3/42 ,  H04L29/06 ,  H04W74/00 ,  G06F15/16 ,  G06F3/033

CPC classification number: G06F17/30867 ,  H04W4/02 ,  H04W4/18

Abstract: Content management architecture for a portable wireless device. Caching and fetching techniques are provided to improve content handling for portable devices such as cellular telephones and portable computers. A search component automatically performs searches as a background process, and potentially desired content is received and cached by a content storing component to be available in the future when and if needed, mitigating latency associated with slow download speeds, refresh rates, and other system and/or network impediments. Content from background search results can be trickled into the device as part of the background process so as not to burden system resources for other processes. As part of memory management, aged and/or low priority or low interest content can be selectively removed or archived to increase available cache or memory space, as well as to maintain relevant content within the device. A presentation component facilitates presentation of the pre-stored content.

Abstract translation: 便携式无线设备的内容管理架构。 提供缓存和提取技术以改进便携式设备（例如蜂窝电话和便携式计算机）的内容处理。 搜索组件自动执行搜索作为后台进程，并且可能期望的内容被内容存储组件接收和缓存，以便将来在需要时可用，减轻与慢下载速度，刷新率和其他系统相关联的延迟，以及 /或网络障碍。 来自后台搜索结果的内容可以作为后台进程的一部分进入设备，以免对其他进程造成系统资源的负担。 作为内存管理的一部分，老化和/或低优先级或低兴趣内容可以被选择性地删除或归档以增加可用的高速缓存或存储器空间，以及维护设备内的相关内容。 演示组件便于显示预存的内容。

公开(公告)号：US08478535B2

公开(公告)日：2013-07-02

申请号：US11324506

申请日：2005-12-30

Applicant: Nebojsa Jojic ,  Vladimir Jojic ,  David E. Heckerman ,  Brendan John Frey ,  Christopher A. Meek

Inventor： Nebojsa Jojic ,  Vladimir Jojic ,  David E. Heckerman ,  Brendan John Frey ,  Christopher A. Meek

IPC: G01N33/50

CPC classification number: G06F19/22 ,  G06F19/14 ,  G06F19/18 ,  G06F19/24 ,  G06G7/48 ,  G06G7/58

Abstract: The subject invention provides systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

Abstract translation: 本发明提供了通过诸如成本函数，贪心算法，期望最大化（EM）算法等机器学习算法来促进艾滋病疫苗鸡尾酒组合的系统和方法。可以利用这种装配来产生疫苗鸡尾酒， 在宿主免疫压力下快速发展的病原体。 例如，本发明的系统和方法可以用于促进用于诸如HIV的病原体的T细胞疫苗的设计。 此外，本发明的系统和方法可以与其他应用相结合使用，例如序列比对，基序发现，分类和重组热点检测。 本文所述的新颖技术可以提供改进，以通过构建具有较高表位覆盖度的疫苗混合物来设计疫苗的传统方法，例如与来自数据的共同体，树节点和随机菌株的鸡尾酒相比。

公开(公告)号：US08290946B2

公开(公告)日：2012-10-16

申请号：US12144647

申请日：2008-06-24

Applicant: Wen-tau Yih ,  Christopher A. Meek

Inventor： Wen-tau Yih ,  Christopher A. Meek

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30687 ,  G06Q30/02

Abstract: Two methods for measuring keyword-document relevance are described. The methods receive a keyword and a document as input and output a probability value for the keyword. The first method is a similarity-based approach which uses techniques for measuring similarity between two short-text segments to measure relevance between the keyword and the document. The second method is a regression-based approach based on an assumption that if an out-of-document phrase (the keyword) is semantically similar to an in-document phrase, then relevance scores of the in and out-of document phrases should be close to each other.

Abstract translation: 描述了两种衡量关键字 - 文档相关性的方法。 方法接收关键字和文档作为输入，并输出关键字的概率值。 第一种方法是基于相似性的方法，其使用用于测量两个短文本段之间的相似性的技术来测量关键字和文档之间的相关性。 第二种方法是基于回归的方法，基于一个假设，如果文档外短语（关键字）在语义上类似于文档内短语，则文本内和外的短语的相关性分数应为 彼此接近

公开(公告)号：US08214890B2

公开(公告)日：2012-07-03

申请号：US12198914

申请日：2008-08-27

Applicant: Darko Kirovski ,  Christopher A. Meek

Inventor： Darko Kirovski ,  Christopher A. Meek

IPC: G06F15/16

CPC classification number: H04L9/3073 ,  H04L9/3234 ,  H04L9/3263 ,  H04L9/3271 ,  H04L63/061 ,  H04L63/0823 ,  H04L63/0853 ,  H04L63/18 ,  H04L2209/56 ,  H04L2209/805 ,  H04L2463/062

Abstract: A user working on a client computer is allowed to remotely login to a server over a computer network. A first secure connection is established between the client and the server. Communications with a trusted device which is in the user's control is established via a communication channel between the trusted device and the client, where this channel is not part of the network. A second secure connection is established between the trusted device and the server through the client, where this second secure connection is tunneled within the first secure connection. The user remotely logs into the server over the second secure connection using the trusted device.

Abstract translation: 允许在客户端计算机上工作的用户通过计算机网络远程登录到服务器。 在客户端和服务器之间建立第一个安全连接。 通过信任设备和客户端之间的通信信道建立与用户控制中的信任设备的通信，其中该信道不是网络的一部分。 通过客户端在可信设备和服务器之间建立第二安全连接，其中该第二安全连接在第一安全连接内被隧道传送。 用户使用受信任的设备通过第二个安全连接远程登录到服务器。

公开(公告)号：US20110314537A1

公开(公告)日：2011-12-22

申请号：US12821124

申请日：2010-06-22

Applicant: Geoffrey J. Hulten ,  Patrice Y. Simard ,  Darko Kirovski ,  Jesper B. Lind ,  Christopher A. Meek

Inventor： Geoffrey J. Hulten ,  Patrice Y. Simard ,  Darko Kirovski ,  Jesper B. Lind ,  Christopher A. Meek

IPC: G06F21/00

CPC classification number: G06F21/30 ,  G06F9/44 ,  G06F21/31 ,  G06F21/577 ,  G06F2221/2133 ,  H04L9/32

Abstract: Human Interaction Proofs (“HIPs”, sometimes referred to as “captchas”), may be generated automatically. An captcha specification language may be defined, which allows a captcha scheme to be defined in terms of how symbols are to be chosen and drawn, and how those symbols are obscured. The language may provide mechanisms to specify the various ways in which to obscure symbols. New captcha schemes may be generated from existing specifications, by using genetic algorithms that combine features from existing captcha schemes that have been successful. Moreover, the likelihood that a captcha scheme has been broken by attackers may be estimated by collecting data on the time that it takes existing captcha schemes to be broken, and using regression to estimate the time to breakage as a function of either the captcha's features or its measured quality.

Abstract translation: 人工交互证明（“HIP”，有时也称为“验证码”）可能会自动生成。 可以定义验证码规范语言，这允许根据如何选择和绘制符号以及这些符号如何被遮蔽来定义验证码方案。 该语言可以提供机制来指定模糊符号的各种方式。 可以通过使用遗传算法从现有规范中生成新的验证码方案，该遗传算法将已经获得成功的现有验证码方案的功能相结合。 此外，验证码计划已被攻击者破坏的可能性可以通过在现有验证码计划被破坏的时间收集数据来估计，并且使用回归来估计作为验证码的特征或函数的破坏时间 其测量质量。

公开(公告)号：US20110219012A1

公开(公告)日：2011-09-08

申请号：US12715417

申请日：2010-03-02

Applicant: Wen-tau Yih ,  Christopher A. Meek ,  Hannaneh Hajishirzi

Inventor： Wen-tau Yih ,  Christopher A. Meek ,  Hannaneh Hajishirzi

IPC: G06F17/30 ,  G06F15/18

CPC classification number: G06F15/18 ,  G06F17/30

Abstract: Described is a technology for measuring the similarity between two objects (e.g., documents), via a framework that learns the term-weighting function from training data, e.g., labeled pairs of objects, to develop a learned model. A learning procedure tunes the model parameters by minimizing a defined loss function of the similarity score. Also described is using the learning procedure and learned model to detect near duplicate documents.

Abstract translation: 描述了一种用于通过从训练数据（例如标记的对象对）学习术语加权函数的框架来测量两个对象（例如，文档）之间的相似性的技术，以开发学习的模型。 学习过程通过最小化相似性得分的定义的损失函数来调整模型参数。 还描述了使用学习过程和学习模型来检测近似重复的文档。

公开(公告)号：US20110214006A1

公开(公告)日：2011-09-01

申请号：US12713195

申请日：2010-02-26

Applicant: Christopher A. Meek ,  Guy Shani

Inventor： Christopher A. Meek ,  Guy Shani

IPC: G06F15/18 ,  G06F11/07

CPC classification number: G06F11/079 ,  G06F11/0709

Abstract: Described is automated learning of failure recovery policies based upon existing information regarding previous policies and actions. A learning mechanism automatically constructs a new policy for controlling a recovery process, based upon collected observable interactions of an existing policy with the process. In one aspect, the learning mechanism builds a partially observable Markov decision process (POMDP) model, and computes the new policy base upon the learned model. The new policy may perform automatic fault recovery, e.g., on a machine in a datacenter corresponding to the controlled process.

Abstract translation: 描述了基于关于先前的策略和动作的现有信息来自动学习故障恢复策略。 学习机制根据现有策略与流程的可观察的交互作用，自动构建一个控制恢复过程的新策略。 在一方面，学习机制构建了部分可观察的马尔可夫决策过程（POMDP）模型，并根据学习模型计算出新的策略基础。 新策略可以执行自动故障恢复，例如在对应于受控进程的数据中心的机器上。

公开(公告)号：US20110107242A1

公开(公告)日：2011-05-05

申请号：US12610392

申请日：2009-11-02

Applicant: Timothy S. Paek ,  Christopher A. Meek

Inventor： Timothy S. Paek ,  Christopher A. Meek

IPC: G06F3/00

CPC classification number: G06Q10/10

Abstract: This patent application pertains to computing scenarios that allow users to more readily accomplish desired tasks. One implementation includes at least one dictionary of potential auto-suggestions that can be generated in relation to user-input. The implementation also includes a text framework configured to weight at least some of the potential auto-suggestions based upon one or more parameters. This implementation further includes a task engine configured to associate tasks with at least some of the potential auto-suggestions.

Abstract translation: 该专利申请涉及允许用户更容易地完成所需任务的计算场景。 一个实现包括可以相对于用户输入生成的潜在的自动建议的至少一个字典。 该实现还包括被配置为基于一个或多个参数来加权至少一些潜在的自动建议的文本框架。 该实现还包括被配置为将任务与至少一些潜在的自动建议相关联的任务引擎。

公开(公告)号：US20100332315A1

公开(公告)日：2010-12-30

申请号：US12492861

申请日：2009-06-26

Applicant: Semiha Ece Kamar ,  Eric Horvitz ,  Christopher A. Meek ,  Stephen Lombardi

Inventor： Semiha Ece Kamar ,  Eric Horvitz ,  Christopher A. Meek ,  Stephen Lombardi

IPC: G06Q30/00 ,  G06F17/10

CPC classification number: G06Q30/0247 ,  G06Q30/02 ,  G06Q30/0254 ,  G06Q30/0261

Abstract: A mobile device may present advertisements to users. However, advertisements may be ineffective or dangerous if presented when the attention of the user is unavailable (e.g., while operating a vehicle at a busy intersection.) It may also be desirable to select a sequence of advertisements that interrelate, or that relate the route of the user to an advertised product or service. Therefore, potential routes may be identified (e.g., based on user history or nearby locations of interest), and for potential routes, advertisement opportunities may be identified where the user may have an at least partial attention availability (e.g., traffic signals and fuel stops.) Advertisements may be selected for presentation at the advertisement opportunities of respective potential routes. Additionally, advertisement opportunities may be offered to advertisers in an auction model, and advertisers may specify conditions of advertisements (e.g., competitive placement exclusive of competitors' advertisements, or combinatorial placement of several advertisements.)

Abstract translation: 移动设备可以向用户呈现广告。 然而，如果在用户的注意不可用时（例如，在繁忙的十字路口操作车辆时），则在广告可能无效或危险的情况下可能是无效的或者危险的。还可能期望选择一系列的广告，这些广告相互关联或涉及路线 用户到广告的产品或服务。 因此，可以识别潜在路线（例如，基于用户历史或附近的兴趣位置），并且对于潜在的路线，可以识别广告机会，其中用户可能具有至少部分注意力可用性（例如，交通信号和燃料停止 可以选择广告来呈现各自潜在路线的广告机会。 此外，可以在拍卖模式中向广告商提供广告机会，并且广告商可以指定广告的条件（例如，排除竞争对手的广告的竞争性布置，或组合放置多个广告）。

公开(公告)号：US07822762B2

公开(公告)日：2010-10-26

申请号：US11427311

申请日：2006-06-28

Applicant: Christopher D. Payne ,  Eric J. Horvitz ,  Alexander G. Gounares ,  Susan T. Dumais ,  Kyle G. Peltonen ,  Gary W. Flake ,  Xuedong D. Huang ,  William H. Gates, III ,  John C. Platt ,  Oliver Hurst-Hiller ,  Joshua T. Goodman ,  Christopher A. Meek ,  Ramez Naam ,  Raymond E Ozzie ,  Eric D. Brill

Inventor： Christopher D. Payne ,  Eric J. Horvitz ,  Alexander G. Gounares ,  Susan T. Dumais ,  Kyle G. Peltonen ,  Gary W. Flake ,  Xuedong D. Huang ,  William H. Gates, III ,  John C. Platt ,  Oliver Hurst-Hiller ,  Joshua T. Goodman ,  Christopher A. Meek ,  Ramez Naam ,  Raymond E Ozzie ,  Eric D. Brill

IPC: G06F7/001

CPC classification number: G06F17/30967 ,  G06F17/30964

Abstract: A system that employs an explicitly and/or implicitly trained model in order to return entity-specific computer-based search results is provided. The innovation can provide for a customized search model that focuses search in connection with achieving information that is meaningful with respect to goals of an entity. The model can be used to modify a search query in accordance with a goal of the entity or to generate the search query thereby returning meaningful and/or targeted results to the user. The system can automatically gather entity-related data thereafter determining or inferring a goal as well as training the model. Moreover, the system can selectively configure (e.g., order, rank, filter) and render results to a user based upon the model.

Abstract translation: 提供了一种采用明确和/或隐含训练的模型以返回基于实体的基于计算机的搜索结果的系统。 该创新可以提供定制的搜索模型，其将搜索重点与获得关于实体目标有意义的信息相关联。 该模型可以用于根据实体的目标修改搜索查询，或者生成搜索查询，从而向用户返回有意义和/或有针对性的结果。 系统可以自动收集与实体有关的数据，然后确定或推断目标以及训练模型。 此外，系统可以基于模型选择性地配置（例如，排序，排序，过滤）并将结果呈现给用户。