公开(公告)号：US20160253684A1

公开(公告)日：2016-09-01

申请号：US14633227

申请日：2015-02-27

Applicant: Google Inc.

Inventor： Huazhong Ning ,  Cheng Sheng ,  Wei Chai ,  Hrishikesh Balkrishna Aradhye

IPC: G06Q30/02

CPC classification number: G06Q30/0201 ,  G06Q30/02 ,  G06Q30/0278

Abstract: Systems and methods of structures reviews through auto-generated tags are provided that include providing, with a computing device having an input device and a display device, a user interface to receive a review for an object from a reviewer, selecting a set of tags from an object tag collection stored in a database communicatively coupled to the computing device according to the object and the reviewer, displaying, by the display device of the computing device, the selected set of tags on a display, receiving an input, by the input device, to remove one or more of the displayed tags, and storing, by a storage device, the remaining tags of the set of tags that are submitted according to the received input for the object.

Abstract translation: 提供了通过自动生成的标签进行结构审查的系统和方法，包括提供具有输入设备和显示设备的计算设备，用于从审阅者接收对象的评论的用户界面，从 存储在根据对象和审阅者通信地耦合到计算设备的数据库中的对象标签集合，通过计算设备的显示设备在显示器上显示所选择的一组标签，由输入设备接收输入 去除一个或多个所显示的标签，并且由存储设备存储根据所接收的对象的输入而提交的一组标签的剩余标签。

公开(公告)号：US20160132783A1

公开(公告)日：2016-05-12

申请号：US14614671

申请日：2015-02-05

Applicant: Google Inc.

Inventor： Huazhong Ning ,  Cheng Sheng ,  Wei Chai

IPC: G06N7/00

CPC classification number: G06N7/005 ,  G06F16/337

Abstract: A system and method of determining sets of related terms in a target domain based on a probability of co-occurrence in a source domain user model and a target domain user model of a same user, creating an adapted user model for a first user based on the sets of related terms, and merging the adapted user model with a target domain user model for the first user to form a merged user model for the first user.

Abstract translation: 一种基于在同一用户的源域用户模型和目标域用户模型中同现的概率来确定目标域中的相关项的集合的系统和方法，其基于以下方式为第一用户创建适配的用户模型： 所述相关术语集合，以及将所述适配用户模型与所述第一用户的目标域用户模型合并，以形成所述第一用户的合并用户模型。

公开(公告)号：US20140317099A1

公开(公告)日：2014-10-23

申请号：US13868533

申请日：2013-04-23

Applicant: GOOGLE INC.

Inventor： Ankit Jain ,  Wei Chai ,  Piotr Zielinski ,  Qisheng Zhao ,  Jindong Chen ,  Anna Patterson ,  Ulas Kirazci ,  Abhinav Khandelwal

IPC: G06F17/30

CPC classification number: G06F16/24578 ,  G06F16/9535

Abstract: Systems and method are disclosed personalizing search results. An example method for personalizing search results may include receiving from a user, a search query for a media item, identifying search results for the search query, and generating a score for each of a plurality of media items identified in the search results. The score for a corresponding one of the plurality of media items may be based on the search query and one or both of a personalized query independent score and/or a personalized query dependent score. The at least one personalized query independent and query dependent scores may be based on at least one media preference signal associated with the user. The search results may be ranked based on the generated score for each of the plurality of media items.

Abstract translation: 披露了个性化搜索结果的系统和方法。 用于个性化搜索结果的示例方法可以包括从用户接收媒体项的搜索查询，识别搜索查询的搜索结果，以及为搜索结果中标识的多个媒体项中的每一个生成分数。 多个媒体项目中对应的一个媒体项目的分数可以基于搜索查询以及个性化查询独立分数和/或个性化查询依赖分数中的一个或两个。 所述至少一个个性化查询独立和查询相关分数可以基于与用户相关联的至少一个媒体偏好信号。 可以基于多个媒体项目中的每一个的生成得分来对搜索结果进行排名。

公开(公告)号：US20140317098A1

公开(公告)日：2014-10-23

申请号：US13868504

申请日：2013-04-23

Applicant: Google Inc.

Inventor： Ankit Jain ,  Wei Chai ,  Anna Patterson ,  Jindong Chen

IPC: G06F17/30

CPC classification number: G06F17/30554 ,  G06Q30/0255 ,  G06Q30/0631

Abstract: Systems and methods are disclosed for determining media consumption preferences. A method may include accessing media consumption history associated with a user. The media consumption history may include at least one of media purchase history of the user, media viewing history of the user, and media listening history of the user. A media category preference of the user may be determined, based on the media consumption history. The media category preference may include a popularity indication for each of a plurality of media categories of media items in the media consumption history. Search results provided in response to a search query by the user and/or media recommendations prepared for the user may be scored based on the media category preference. The media may include a video, a movie, a TV show, a book, an audio recording, a music album and/or another type of digital media.

Abstract translation: 公开了用于确定媒体消费偏好的系统和方法。 方法可以包括访问与用户相关联的媒体消费历史。 媒体消费历史可以包括用户的媒体购买历史，用户的媒体观看历史和用户的媒体收听历史中的至少一个。 可以基于媒体消费历史来确定用户的媒体类别偏好。 媒体类别偏好可以包括媒体消费历史中媒体项目的多个媒体类别中的每一个的流行度指示。 响应于用户的搜索查询提供的搜索结果和/或为用户准备的媒体推荐可以基于媒体类别偏好来评分。 媒体可以包括视频，电影，电视节目，书，音频记录，音乐相册和/或其他类型的数字媒体。

公开(公告)号：US20170300814A1

公开(公告)日：2017-10-19

申请号：US15394668

申请日：2016-12-29

Applicant: Google Inc.

Inventor： Tal Shaked ,  Rohan Anil ,  Hrishikesh Balkrishna Aradhye ,  Mustafa Ispir ,  Glen Anderson ,  Wei Chai ,  Mehmet Levent Koc ,  Jeremiah Harmsen ,  Xiaobing Liu ,  Gregory Sean Corrado ,  Tushar Deepak Chandra ,  Heng-Tze Cheng

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/084

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

公开(公告)号：US09607314B1

公开(公告)日：2017-03-28

申请号：US15066225

申请日：2016-03-10

Applicant: Google Inc.

Inventor： Gaofeng Zhao ,  Yingwei Cui ,  Hui Tan ,  Bahman Rabii ,  Wei Chai

IPC: G06F17/00 ,  G06Q30/02

CPC classification number: G06Q30/0249 ,  G06F17/2247 ,  G06F17/30867 ,  G06Q30/0246 ,  G06Q30/0253 ,  G06Q30/0256 ,  G06Q30/0277

Abstract: Systems and methods of evaluating information in a computer network environment are provided. A data processing system can obtain or receive a content placement criterion, such as a keyword, associated with a content item and can determine a quality metric of the content placement criterion. The data processing system can identify a candidate content placement criterion and expand placement criteria associated with the content item to include the content placement criterion and the candidate content placement criterion based at least in part on an evaluation of the quality metric of the content placement criterion. The data processing system can expand placement criteria based in part on a throttling parameter. The data processing system can identify a correlation between a document and the placement criteria to identify appropriate content items for the document.

公开(公告)号：US09547698B2

公开(公告)日：2017-01-17

申请号：US13868504

申请日：2013-04-23

Applicant: Google Inc.

Inventor： Ankit Jain ,  Wei Chai ,  Anna Patterson ,  Jindong Chen

IPC: G06F17/30 ,  G06Q30/02 ,  G06Q30/06

CPC classification number: G06F17/30554 ,  G06Q30/0255 ,  G06Q30/0631

Abstract: Systems and methods are disclosed for determining media consumption preferences. A method may include accessing media consumption history associated with a user. The media consumption history may include at least one of media purchase history of the user, media viewing history of the user, and media listening history of the user. A media category preference of the user may be determined, based on the media consumption history. The media category preference may include a popularity indication for each of a plurality of media categories of media items in the media consumption history. Search results provided in response to a search query by the user and/or media recommendations prepared for the user may be scored based on the media category preference. The media may include a video, a movie, a TV show, a book, an audio recording, a music album and/or another type of digital media.

Abstract translation: 公开了用于确定媒体消费偏好的系统和方法。 方法可以包括访问与用户相关联的媒体消费历史。 媒体消费历史可以包括用户的媒体购买历史，用户的媒体观看历史和用户的媒体收听历史中的至少一个。 可以基于媒体消费历史来确定用户的媒体类别偏好。 媒体类别偏好可以包括媒体消费历史中媒体项目的多个媒体类别中的每一个的流行度指示。 响应于用户的搜索查询提供的搜索结果和/或为用户准备的媒体推荐可以基于媒体类别偏好来评分。 媒体可以包括视频，电影，电视节目，书，音频记录，音乐相册和/或其他类型的数字媒体。

公开(公告)号：US09311384B1

公开(公告)日：2016-04-12

申请号：US13788251

申请日：2013-03-07

Applicant: Google Inc.

Inventor： Ankit Jain ,  Wei Chai

IPC: G06F17/30

CPC classification number: G06F17/30595 ,  G06F17/30861

Abstract: A server system, which manages distribution or download of content, may obtain data relating to interactions between a user and one or more other server systems providing services that are different from services provided by the server system. The server system may then analyze the obtained interactions related data, with the analysis comprising identifying content accessed, obtained, or used by the user during the interactions between the user and the one or more other server systems. The server system may then map that content to one or more other contents available in the server system, and may generate, based on that mapping, recommendation information personalized for the user.

Abstract translation: 管理内容的分发或下载的服务器系统可以获得与用户和提供与服务器系统提供的服务不同的服务的一个或多个其他服务器系统之间的交互相关的数据。 然后，服务器系统可以分析获得的交互相关数据，分析包括识别用户在一个或多个其他服务器系统之间的交互期间被用户访问，获取或使用的内容。 然后，服务器系统可以将该内容映射到服务器系统中可用的一个或多个其他内容，并且可以基于该映射生成为用户个性化的推荐信息。