公开(公告)号：US09449339B2

公开(公告)日：2016-09-20

申请号：US14578596

申请日：2014-12-22

Applicant: Google Inc.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G06F15/173 ,  G06Q30/06 ,  H04L12/26

CPC classification number: G06Q30/0631 ,  H04L43/04 ,  H04L67/22

Abstract: An electronic device may generate use related information and resource consumption related information corresponding to each of used applications used in the electronic device. The use related information and the resource consumption related information may then be transmitted to a remote applications manager, which may analyze the information to generate, based on the analysis, specially tailored application recommendations. The application recommendations may list one or more other applications, newly available or offered, which may be recommended for download to and/or use in the electronic device. The analysis of the use and the resource consumption information may comprise ranking the used applications, such as based on use patterns and/or resource consumption, and/or classification of the used applications, such as based on application type. Generating the application recommendations may comprise correlating used applications, based on classification and/or ranking, with similar applications that may be recommended.

公开(公告)号：US20150262232A1

公开(公告)日：2015-09-17

申请号：US13686636

申请日：2012-11-27

Applicant: Google Inc.

Inventor： Daniel Victor Klein ,  Dean Kenneth Jackson

IPC: G06Q30/02

CPC classification number: G06Q30/0255

Abstract: Methods and systems are provided for selecting and serving content, such as promotional content, to a user in accordance with a shopping interest of the user, location information for the user (e.g., location information associated with the user's mobile device), or both. A content delivery system is configured to make inferences on which promotional content to deliver to a user based on different types of signals. These signals include, for example, regular geolocation signals (e.g., GPS), fine-grained geolocation signals (e.g., DGPS, site-specific or site-provided signals, etc.), near-field communication (NFC) signals, purchase information signals, browsing history signals, and any combination of such signals. A shopping interest of a user is determined based on location information and/or transaction information indicating whether or not the user has not conducted a related transaction in a time period.

Abstract translation: 提供方法和系统，用于根据用户的购物兴趣，用户的位置信息（例如，与用户的移动设备相关联的位置信息）或两者来选择和向用户提供诸如促销内容的内容。 内容递送系统被配置为基于不同类型的信号来推断要向用户传递哪些宣传内容。 这些信号包括例如常规地理位置信号（例如，GPS），细粒度地理位置信号（例如，DGPS，场地特定或站点提供的信号等），近场通信（NFC）信号，购买信息 信号，浏览历史信号以及这些信号的任何组合。 基于位置信息和/或指示用户是否在一段时间内没有进行相关交易的交易信息确定用户的购物兴趣。

公开(公告)号：US20140201246A1

公开(公告)日：2014-07-17

申请号：US13904800

申请日：2013-05-29

Applicant: Google Inc.

Inventor： Daniel Victor Klein ,  Dean Kenneth Jackson

IPC: G06F17/30

CPC classification number: G06Q10/10 ,  G06Q50/01

Abstract: Implementations of the present disclosure provide for constructing crowd-sourced global contact lists and for providing caller identification functions. Additional implementations of the present disclosure provide for providing spam identification. The systems and methods described herein contemplate aggregating the information stored in multiple local contact lists. The systems and methods further contemplate analyzing and processing the aggregated information in order to construct a global contact list. The analyzing and processing may involve identifying each phone number appearing in any of the local contact lists, identifying all fields associated with those phone numbers, and identifying, for each field contained in the local contact lists, an entry for which the local contact lists exhibit a threshold degree of consensus. The global contact list created from the aggregation of information from local contact lists can be employed to provide caller identification and spam identification features.

Abstract translation: 本公开的实施方案提供构建人群来源的全球联系人列表和用于提供呼叫者识别功能。 本公开的附加实施例提供了提供垃圾邮件标识。 本文描述的系统和方法考虑聚合存储在多个本地联系人列表中的信息。 系统和方法进一步考虑分析和处理聚合信息以构建全局联系人列表。 分析和处理可以包括识别出现在任何本地联系人列表中的每个电话号码，识别与这些电话号码相关联的所有字段，以及为本地联系人列表中包含的每个字段标识本地联系人列表所显示的条目 达成一致的程度。 可以使用从本地联系人列表中的信息聚合创建的全局联系人列表来提供呼叫者识别和垃圾邮件标识功能。

公开(公告)号：US10306010B2

公开(公告)日：2019-05-28

申请号：US15297501

申请日：2016-10-19

Applicant: Google Inc.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G06F15/16 ,  H04L29/08 ,  G06F15/173 ,  G06Q10/10 ,  G06F16/2457 ,  G06Q50/00 ,  H04L12/58

Abstract: Implementations of the disclosure describe inferring social groups through patterns of communication. A method of the disclosure includes ascertaining, by a processing device, a proposed group of contacts from contacts of the user based on a correlation in geographic locations of communications between the user and the proposed group of contacts and a correlation in a type of medium of the communications, providing a recommendation that the user create a new list of contacts associated with the user from the proposed group of contacts, and responsive to the user indicating acceptance of the recommendation, creating the new list of contacts associated with the user from the proposed group.

公开(公告)号：US09870298B2

公开(公告)日：2018-01-16

申请号：US13975719

申请日：2013-08-26

Applicant: Google Inc.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G06F9/46 ,  G06F11/34 ,  G06F9/52 ,  G06F11/07 ,  G06Q30/06 ,  H04W4/00 ,  G06F9/445

CPC classification number: G06F11/3433 ,  G06F8/62 ,  G06F8/65 ,  G06F9/44552 ,  G06F9/52 ,  G06F11/0742 ,  G06F11/0793 ,  G06F11/3409 ,  G06Q30/0601 ,  H04W4/50 ,  H04W4/60

Abstract: Methods and systems for automatically identifying an application that is experiencing performance problems caused by a resource utilization event may include receiving an indication that an application is experiencing a performance issue. It may be determined that the performance issue is caused by a resource utilization event on a device. The resource utilization event may include the application and one or more other applications running simultaneously, use of one or more functions of the device simultaneously by at least one of the first application and one or more other applications, and/or a resource utilization overload based on simultaneous use of a plurality of sensors on the device. Next, action may be taken to correct the performance issue of the application.

公开(公告)号：US09329047B2

公开(公告)日：2016-05-03

申请号：US14060337

申请日：2013-10-22

Applicant: GOOGLE INC.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G01C21/34 ,  G01C21/36 ,  G01C21/00 ,  H04W4/00 ,  H04W4/02

CPC classification number: G01C21/343 ,  G01C21/00 ,  G01C21/34 ,  G01C21/3617 ,  G01C21/3679 ,  G01C21/3691 ,  H04W4/029

Abstract: A latency analysis system determines a latency period, such as a wait time, at a user destination. To determine the latency period, the latency analysis system receives location history from multiple user devices. With the location histories, the latency analysis system identifies points-of-interest that users have visited and determines the amount of time the user devices were at a point-of-interest. For example, the latency analysis system determines when a user device entered and exited a point-of-interest. Based on the elapsed time between entry and exit, the latency analysis system determines how long the user device was inside the point-of-interest. By averaging elapsed times for multiple user devices, the latency analysis system determines a latency period for the point-of-interest. The latency analysis system then uses the latency period to provide latency-based recommendations to a user. For example, the latency analysis system may determine a shopping route for a user.

Abstract translation: 延迟分析系统在用户目的地确定等待时间，例如等待时间。 为了确定延迟时间，延迟分析系统从多个用户设备接收位置历史记录。 利用位置历史，延迟分析系统识别用户访问的兴趣点，并确定用户设备处于兴趣点的时间量。 例如，延迟分析系统确定用户设备何时进入并退出兴趣点。 基于进入和退出之间的经过时间，延迟分析系统确定用户设备在兴趣点之内的时间长短。 通过平均多个用户设备的经过时间，延迟分析系统确定兴趣点的等待时间。 延迟分析系统然后使用延迟时间为用户提供基于延迟的推荐。 例如，延迟分析系统可以确定用户的购物路线。

公开(公告)号：US20150185032A1

公开(公告)日：2015-07-02

申请号：US14644982

申请日：2015-03-11

Applicant: GOOGLE INC.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G01C21/34 ,  H04W4/02

CPC classification number: G01C21/343 ,  G01C21/00 ,  G01C21/34 ,  G01C21/3617 ,  G01C21/3679 ,  G01C21/3691 ,  H04W4/029

Abstract: A latency analysis system determines a latency period, such as a wait time, at a user destination. To determine the latency period, the latency analysis system receives location history from multiple user devices. With the location histories, the latency analysis system identifies points-of-interest that users have visited and determines the amount of time the user devices were at a point-of-interest. For example, the latency analysis system determines when a user device entered and exited a point-of-interest. Based on the elapsed time between entry and exit, the latency analysis system determines how long the user device was inside the point-of-interest. By averaging elapsed times for multiple user devices, the latency analysis system determines a latency period for the point-of-interest. The latency analysis system then uses the latency period to provide latency-based recommendations to a user. For example, the latency analysis system may determine a shopping route for a user.

公开(公告)号：US20150110464A1

公开(公告)日：2015-04-23

申请号：US14584331

申请日：2014-12-29

Applicant: Google Inc.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: H04N5/445 ,  H04N21/845 ,  H04N21/475 ,  H04N21/488 ,  H04N21/44 ,  H04N21/472

CPC classification number: H04N5/44513 ,  H04N5/44543 ,  H04N21/44008 ,  H04N21/44222 ,  H04N21/4622 ,  H04N21/47214 ,  H04N21/47217 ,  H04N21/4755 ,  H04N21/4882 ,  H04N21/8456

Abstract: Systems and methods for customizing video include providing a portion of video to an electronic display and identifying a character or personality in the portion of video. A request to perform an action regarding the portion of video may be detected and the action may be associated with the identified character or personality. The action may be performed on a second portion of video in response to the character or personality being identified in the second portion of video.

Abstract translation: 用于定制视频的系统和方法包括将视频的一部分提供给电子显示器并且识别视频部分中的角色或个性。 可以检测到关于视频部分执行动作的请求，并且该动作可以与所识别的角色或个性相关联。 响应于在视频的第二部分中识别的角色或个性，可以在视频的第二部分上执行动作。

公开(公告)号：US20150058357A1

公开(公告)日：2015-02-26

申请号：US13668130

申请日：2012-11-02

Applicant: Google Inc.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G06F17/30

CPC classification number: G06F16/337 ,  G06F16/29 ,  G06F16/9535

Abstract: The subject technology discloses configurations for accessing one or more entries of rating information for a place associated with a geographical location; identifying, using one or more criteria, a type of user that authored each of the accessed one or more entries of rating information for the place; for a user viewing the one or more entries of rating information for the place, identifying, using one or more criteria, a type of user that is viewing the accessed one or more entries of rating information for the place; filtering the accessed one or more entries of rating information for the place according to the type of user that authored each of the accessed entries and the type of user that is viewing the accessed entries; and providing for display the filtered one or more entries of rating information for the place.

Abstract translation: 主题技术公开了用于访问与地理位置相关联的地点的评级信息的一个或多个条目的配置; 使用一个或多个标准来识别为所述地点的所述一个或多个访问的评估信息的每一个创建的用户的类型; 对于查看该地点的评级信息的一个或多个条目的用户，使用一个或多个标准来识别正在查看所访问的一个或多个该地点的评级信息条目的用户类型; 根据创建每个访问条目的用户类型和正在查看访问条目的用户类型，过滤所访问的一个或多个评级信息条目; 并提供显示过滤的一个或多个该地点的评级信息条目。

公开(公告)号：US20150025799A1

公开(公告)日：2015-01-22

申请号：US14060337

申请日：2013-10-22

Applicant: GOOGLE INC.

Inventor： Dean Kenneth Jackson ,  Daniel Victor Klein

IPC: G01C21/00

CPC classification number: G01C21/343 ,  G01C21/00 ,  G01C21/34 ,  G01C21/3617 ,  G01C21/3679 ,  G01C21/3691 ,  H04W4/029

Abstract: A latency analysis system determines a latency period, such as a wait time, at a user destination. To determine the latency period, the latency analysis system receives location history from multiple user devices. With the location histories, the latency analysis system identifies points-of-interest that users have visited and determines the amount of time the user devices were at a point-of-interest. For example, the latency analysis system determines when a user device entered and exited a point-of-interest. Based on the elapsed time between entry and exit, the latency analysis system determines how long the user device was inside the point-of-interest. By averaging elapsed times for multiple user devices, the latency analysis system determines a latency period for the point-of-interest. The latency analysis system then uses the latency period to provide latency-based recommendations to a user. For example, the latency analysis system may determine a shopping route for a user.

Abstract translation: 延迟分析系统在用户目的地确定等待时间，例如等待时间。 为了确定延迟时间，延迟分析系统从多个用户设备接收位置历史记录。 利用位置历史，延迟分析系统识别用户访问的兴趣点，并确定用户设备处于兴趣点的时间量。 例如，延迟分析系统确定用户设备何时进入并退出兴趣点。 基于进入和退出之间的经过时间，延迟分析系统确定用户设备在兴趣点之内的时间长短。 通过平均多个用户设备的经过时间，延迟分析系统确定兴趣点的等待时间。 延迟分析系统然后使用延迟时间为用户提供基于延迟的推荐。 例如，延迟分析系统可以确定用户的购物路线。