公开(公告)号：US20160132780A1

公开(公告)日：2016-05-12

申请号：US14539777

申请日：2014-11-12

Applicant: Google Inc.

Inventor： Hrishikesh Aradhye ,  Atul Kumar

IPC: G06N5/04 ,  H04L29/08

CPC classification number: G06N5/048 ,  G06Q30/02 ,  H04L67/10

Abstract: Images and/or videos may be recommended to a developer based on a classifier. The classifier may determine an application metric that may measure the likelihood that an application is successful for applications on an application store. The system may extract and/or determine features from images and/or videos associated with a training set of applications that are deemed successful. A classifier may be trained on the training set of applications to determine which features of the images and/or videos are associated with the application metric. The classifier may be applied to new and/or existing applications on the application store to generate a recommendation of which images the developer of the application should use to increase the likelihood that the application will be successful.

Abstract translation: 基于分类器，可能会向开发人员推荐图像和/或视频。 分类器可以确定可以测量应用对应用商店上的应用成功的可能性的应用度量。 系统可以从被认为是成功的应用程序的训练集相关联的图像和/或视频中提取和/或确定特征。 可以对训练集应用程序对分类器进行训练，以确定图像和/或视频的哪些特征与应用度量相关联。 分类器可以应用于应用商店上的新的和/或现有的应用程序，以产生应用程序开发人员应该使用哪些图像来增加应用程序成功的可能性的建议。

公开(公告)号：US20140229880A1

公开(公告)日：2014-08-14

申请号：US14258996

申请日：2014-04-22

Applicant: Google Inc.

Inventor： Hrishikesh Aradhye ,  Wei Hua ,  Ruei-Sung Lin ,  Mohammed Saberian

IPC: G06F17/30

CPC classification number: G06F17/3053 ,  G06F3/0481 ,  G06F3/0482 ,  G06Q10/107 ,  H04L51/24 ,  H04L51/26 ,  H04L51/38

Abstract: Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.

Abstract translation: 所公开技术的某些实施例包括用于使用机器学习确定移动设备上的通知的优先级的系统和方法。 所公开技术的其他方面包括基于通知的优先级选择性地显示通知。 根据所公开的技术的实施例，提供了一种计算机实现方法，其包括向可操作地耦合到移动设备的显示设备输出多个通知，其中来自所述多个通知的每个相应的通知与相应的 优先分数 由所述移动设备修改基于响应于来自所述多个通知的第一通知接收到的用户输入和来自所述多个通知的第二通知的特征的排序模型; 基于所述修改的排序模型，由所述移动设备确定与第三通知相关联的优先级得分; 以及基于与所述第三通知相关联的优先级得分将所述第三通知输出到所述显示设备，其中所述第三通知响应于与所述第三通知相关联的优先级得分大于至少一个与 来自多个通知的对应的相应通知。

公开(公告)号：US08707201B1

公开(公告)日：2014-04-22

申请号：US13648972

申请日：2012-10-10

Applicant: Google Inc.

Inventor： Hrishikesh Aradhye ,  Wei Hua ,  Ruei-sung Lin ,  Mohammad Saberian

IPC: G06F3/048 ,  G06F3/0481 ,  G06F3/0482

CPC classification number: G06F17/3053 ,  G06F3/0481 ,  G06F3/0482 ,  G06Q10/107 ,  H04L51/24 ,  H04L51/26 ,  H04L51/38

Abstract: Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.

Abstract translation: 所公开技术的某些实施例包括用于使用机器学习确定移动设备上的通知的优先级的系统和方法。 所公开技术的其他方面包括基于通知的优先级选择性地显示通知。 根据所公开的技术的实施例，提供了一种计算机实现方法，其包括向可操作地耦合到移动设备的显示设备输出多个通知，其中来自所述多个通知的每个相应通知与相应的 优先分数 由所述移动设备修改基于响应于来自所述多个通知的第一通知接收到的用户输入和来自所述多个通知的第二通知的特征的排序模型; 确定，由所述移动设备，其中基于修改的排名模型的第三通知相关联的优先级分数; 并输出到显示装置，基于与所述第三通知，相关联的优先级得分的第三通知，其中，所述第三通知被图形强调响应于与所述第三通知比与相关联的至少一个各自的优先级得分更大的相关联的优先级得分 从所述多个通知对应的相应通知。

公开(公告)号：US20220004929A1

公开(公告)日：2022-01-06

申请号：US17479364

申请日：2021-09-20

Applicant: Google Inc.

Inventor： Pannag Sanketi ,  Wolfgang Grieskamp ,  Daniel Ramage ,  Hrishikesh Aradhye ,  Shiyu Hu

IPC: G06N20/00 ,  G06N5/04

Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.

公开(公告)号：US10242080B1

公开(公告)日：2019-03-26

申请号：US14084816

申请日：2013-11-20

Applicant: GOOGLE INC.

Inventor： Gabriel Cohen ,  Hrishikesh Aradhye

IPC: G06F17/30

Abstract: The present disclosure provides a system and method for automatic clustering and recognition of software applications using metadata. The system selects and extracts visual features from software applications which are then classified, analyzed using a cluster analysis, and then used to assign the software application to a cluster group.

公开(公告)号：US09817869B2

公开(公告)日：2017-11-14

申请号：US14258996

申请日：2014-04-22

Applicant: Google Inc.

Inventor： Hrishikesh Aradhye ,  Wei Hua ,  Ruei-Sung Lin ,  Mohammed Saberian

IPC: G06F3/048 ,  G06F17/30 ,  G06F3/0481 ,  G06F3/0482 ,  G06Q10/10 ,  H04L12/58

CPC classification number: G06F17/3053 ,  G06F3/0481 ,  G06F3/0482 ,  G06Q10/107 ,  H04L51/24 ,  H04L51/26 ,  H04L51/38

Abstract: Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.

公开(公告)号：US20160299972A1

公开(公告)日：2016-10-13

申请号：US15092459

申请日：2016-04-06

Applicant: Google Inc.

Inventor： Rajhans Samdani ,  Amarnag Subramanya ,  Fernando Pereira ,  Hrishikesh Aradhye

IPC: G06F17/30 ,  G06F17/22 ,  H04L29/08

CPC classification number: G06F16/951 ,  G06F16/24534 ,  G06F16/24573 ,  G06F16/95 ,  G06F17/2235 ,  H04L67/02

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing app store search results. An example method includes responsive to a first search query directed to an app store: revising the first search query to produce a second search query different from the first search query; obtaining, from an Internet search engine, second search results responsive to the second search query; analyzing the second search results to identify apps available on the app store that are relevant to the second search query; obtaining, from the app store, first search results responsive to the first search query that identify apps available in the app store; and modifying the first search results based on analyzing the second search results.

Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于提供应用商店搜索结果。 示例性方法包括响应于针对应用商店的第一搜索查询：修改第一搜索查询以产生与第一搜索查询不同的第二搜索查询; 从互联网搜索引擎获得响应于所述第二搜索查询的第二搜索结果; 分析第二搜索结果以识别应用商店上可用于与第二搜索查询相关的应用; 从应用商店获得响应于识别应用商店中可用的应用的第一搜索查询的第一搜索结果; 以及基于分析所述第二搜索结果来修改所述第一搜索结果。

公开(公告)号：US20150081604A1

公开(公告)日：2015-03-19

申请号：US14552001

申请日：2014-11-24

Applicant: Google Inc.

Inventor： Juan Carlos Niebles Duque ,  Hrishikesh Aradhye ,  Luciano Sbaiz ,  Jay Yagnik ,  Reto Strobl

IPC: G06N5/04 ,  G06N99/00

CPC classification number: G06N99/005 ,  G06F17/30781 ,  G06K9/00744 ,  H04L65/4084 ,  H04N21/23418 ,  H04N21/252 ,  H04N21/25883 ,  H04N21/25891

Abstract: A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.

Abstract translation: 人口统计学分析训练分类器模型，用于预测未知人口统计信息的视频和用户的人口特性值。 在一个实施例中，人口统计分析系统训练分类器模型，以使用诸如视频上传者的人口统计学，文本元数据和/或视频的视听内容的视频特征来预测视频的人口统计。 在一个实施例中，人口统计分析系统训练分类器模型，以基于用户的先前视频观看时段使用用户特征来预测用户（例如，匿名用户）的人口统计。 例如，基于观看期的用户特征可以包括个体观看期间统计，例如观看的总视频。 此外，基于观看期间的特征可以包括在观看期间的值的分布，诸如视频上传者的人口统计属性值中的分布，和/或一天中的几天，星期几等的观看次数分布。