公开(公告)号：US10289296B1

公开(公告)日：2019-05-14

申请号：US15018667

申请日：2016-02-08

Applicant: Google Inc.

Inventor： Kun Zhang ,  Willa Angel Chen ,  Yingwei Cui ,  William Martin Halpin, Jr. ,  Bahman Rabii ,  Tobias Maurer

IPC: G06F3/0485 ,  G06F17/22

Abstract: Method and systems for displaying content items on an information resource include identifying a supplemental content item to append to a DOM tree of the information resource and identifying a first content item displayed in a first container of the information resource. The methods also includes monitoring a position of a predetermined portion of the first content item relative to a viewport of the application and determining, responsive to monitoring the position of the predetermined portion of the first content item, that the first content item is visible within the viewport of the application. The method also includes appending the supplemental content item in a second container at a first position between the first container and an end of the information resource and displaying the supplemental content item within the viewport of the application responsive to detecting a scroll action towards the end of the information resource.

公开(公告)号：US20150012926A1

公开(公告)日：2015-01-08

申请号：US14490542

申请日：2014-09-18

Applicant: Google Inc.

Inventor： Li Wei ,  Kun Zhang ,  Yu He ,  Xinmei Cai

IPC: H04N21/2668 ,  H04N21/482 ,  H04N21/442 ,  H04N21/262

CPC classification number: H04N21/2668 ,  G06F17/30828 ,  G06N5/00 ,  G06N5/04 ,  H04N21/26258 ,  H04N21/44222 ,  H04N21/4826

Abstract: A system and method provides video recommendations for a target video in a video sharing environment. The system selects one or more videos that are on one or more video playlists together with the target video. The video co-occurrence data of the target video associates the target video and another video on one or more same video playlists and frequency of the target video and another video on the video playlists is computed. Based on the video co-occurrence data of the target video, one or more co-occurrence videos are selected and ranked based on the video co-occurrence data of the target video. The system selects one or more videos from the co-occurrence videos as video recommendations for the target video.

Abstract translation: 系统和方法在视频共享环境中为目标视频提供视频推荐。 该系统与目标视频一起选择一个或多个视频播放列表上的一个或多个视频。 目标视频的视频同现数据在一个或多个相同的视频播放列表上将目标视频和另一视频相关联，并且计算目标视频的频率和视频播放列表上的另一视频。 基于目标视频的视频同现数据，基于目标视频的视频同现数据来选择和排列一个或多个同现视频。 该系统从共同视频中选择一个或多个视频作为目标视频的视频推荐。

公开(公告)号：US10585576B2

公开(公告)日：2020-03-10

申请号：US15014795

申请日：2016-02-03

Applicant: Google Inc.

Inventor： Tianjiu Yin ,  Kun Zhang

IPC: G06F3/048 ,  G06F3/0485 ,  G06F3/0483 ,  G06F3/0488 ,  G06F9/451

Abstract: Systems and methods for attributing a scroll event are described herein. The system can provide, to a client device, an infinite scroll attribution script. The script can cause the client device to set a dimension of an inline frame, embedded with a content document, of an page to a dimension corresponding to a viewport of an application and determine, responsive to detecting a scroll event, that a first offset between a first content document end and a first viewport end is less than or equal to a first predetermined threshold. The script can further cause the client device to determine, responsive to detecting the scroll event, that a second offset between a second content document end and a second viewport end is greater than or equal to a second threshold and assign the scroll event to the inline frame responsive to the determinations of the first and second offsets.

公开(公告)号：US20190034591A1

公开(公告)日：2019-01-31

申请号：US15690721

申请日：2017-08-30

Applicant: Google Inc.

Inventor： Alexander Mossin ,  Alvin Rajkomar ,  Eyal Oren ,  James Wilson ,  James Wexler ,  Patrik Sundberg ,  Andrew Dai ,  Yingwei Cui ,  Gregory Corrado ,  Hector Yee ,  Jacob Marcus ,  Jeffrey Dean ,  Benjamin Irvine ,  Kai Chen ,  Kun Zhang ,  Michaela Hardt ,  Xiaomi Sun ,  Nissan Hajaj ,  Peter Liu ,  Quoc Le ,  Xiaobing Liu ,  Yi Zhang

IPC: G06F19/00 ,  G06N3/08 ,  G06N3/04

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

公开(公告)号：US20190034590A1

公开(公告)日：2019-01-31

申请号：US15690714

申请日：2017-08-30

Applicant: Google Inc.

Inventor： Eyal Oren ,  Yingwei Cui ,  Gerardo Flores ,  Gavin Duggan ,  Kun Zhang ,  Kurt Litsch ,  Patrik Sundberg ,  Yi Zhang

IPC: G06F19/00 ,  G06N3/08

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

公开(公告)号：US20170115842A1

公开(公告)日：2017-04-27

申请号：US15014795

申请日：2016-02-03

Applicant: Google Inc.

Inventor： Tianjiu Yin ,  Kun Zhang

IPC: G06F3/0485

Abstract: Systems and methods for attributing a scroll event are described herein. The system can provide, to a client device, an infinite scroll attribution script. The script can cause the client device to set a dimension of an inline frame, embedded with a content document, of an page to a dimension corresponding to a viewport of an application and determine, responsive to detecting a scroll event, that a first offset between a first content document end and a first viewport end is less than or equal to a first predetermined threshold. The script can further cause the client device to determine, responsive to detecting the scroll event, that a second offset between a second content document end and a second viewport end is greater than or equal to a second threshold and assign the scroll event to the inline frame responsive to the determinations of the first and second offsets.

公开(公告)号：US09141906B2

公开(公告)日：2015-09-22

申请号：US13802184

申请日：2013-03-13

Applicant: Google Inc.

Inventor： Kai Chen ,  Xiaodan Song ,  Gregory S. Corrado ,  Kun Zhang ,  Jeffrey A. Dean ,  Bahman Rabii

IPC: G06F15/18 ,  G06E1/00 ,  G06E3/00 ,  G06G7/00 ,  G06N3/08 ,  G06F17/30 ,  G06N3/04 ,  G06Q30/02

CPC classification number: G06N3/084 ,  G06F17/30707 ,  G06F17/30864 ,  G06N3/04 ,  G06N3/0427 ,  G06N3/08 ,  G06Q30/02

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring concept terms using a deep network. One of the methods includes receiving an input comprising a plurality of features of a resource, wherein each feature is a value of a respective attribute of the resource; processing each of the features using a respective embedding function to generate one or more numeric values; processing the numeric values to generate an alternative representation of the features of the resource, wherein processing the floating point values comprises applying one or more non-linear transformations to the floating point values; and processing the alternative representation of the input to generate a respective relevance score for each concept term in a pre-determined set of concept terms, wherein each of the respective relevance scores measures a predicted relevance of the corresponding concept term to the resource.

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，用于使用深层网络评分概念术语。 所述方法之一包括接收包括资源的多个特征的输入，其中每个特征是所述资源的相应属性的值; 使用相应的嵌入功能处理每个特征以生成一个或多个数值; 处理所述数值以产生所述资源的特征的替代表示，其中处理所述浮点值包括将一个或多个非线性变换应用于所述浮点值; 以及处理所述输入的替代表示以在预定概念术语集合中为每个概念项产生相应的相关性得分，其中各个相关性分数中的每一个测量相应概念项与所述资源的预测相关性。

公开(公告)号：US09479811B2

公开(公告)日：2016-10-25

申请号：US14490542

申请日：2014-09-18

Applicant: Google Inc.

Inventor： Li Wei ,  Kun Zhang ,  Yu He ,  Xinmei Cai

IPC: G06N5/00 ,  H04N21/2668 ,  G06N5/04 ,  H04N21/262 ,  H04N21/442 ,  H04N21/482 ,  G06F17/30

CPC classification number: H04N21/2668 ,  G06F17/30828 ,  G06N5/00 ,  G06N5/04 ,  H04N21/26258 ,  H04N21/44222 ,  H04N21/4826

Abstract: A system and method provides video recommendations for a target video in a video sharing environment. The system selects one or more videos that are on one or more video playlists together with the target video. The video co-occurrence data of the target video associates the target video and another video on one or more same video playlists and frequency of the target video and another video on the video playlists is computed. Based on the video co-occurrence data of the target video, one or more co-occurrence videos are selected and ranked based on the video co-occurrence data of the target video. The system selects one or more videos from the co-occurrence videos as video recommendations for the target video.

Abstract translation: 系统和方法在视频共享环境中为目标视频提供视频推荐。 该系统与目标视频一起选择一个或多个视频播放列表上的一个或多个视频。 目标视频的视频同现数据在一个或多个相同的视频播放列表上将目标视频和另一视频相关联，并且计算目标视频的频率和视频播放列表上的另一视频。 基于目标视频的视频同现数据，基于目标视频的视频同现数据来选择和排列一个或多个同现视频。 该系统从共同视频中选择一个或多个视频作为目标视频的视频推荐。

公开(公告)号：US09465435B1

公开(公告)日：2016-10-11

申请号：US13975974

申请日：2013-08-26

Applicant: Google Inc.

Inventor： Kun Zhang ,  Yu He

IPC: G06F3/01 ,  H04N21/25 ,  H04N21/258 ,  H04N21/422 ,  H04N21/4223 ,  H04N21/45 ,  H04N21/658 ,  H04N21/845 ,  H04N21/8549

CPC classification number: H04N21/44222 ,  G06F3/01 ,  H04N21/252 ,  H04N21/25883 ,  H04N21/42201 ,  H04N21/42202 ,  H04N21/42203 ,  H04N21/4223 ,  H04N21/4312 ,  H04N21/4345 ,  H04N21/44 ,  H04N21/4532 ,  H04N21/6582 ,  H04N21/8456 ,  H04N21/8549

Abstract: Systems and methods for segmenting a video based on user engagement in respective segments of the video are presented. In one or more aspects, a system is provided that includes an engagement component configured to receive information regarding respective engagement of a plurality of users in connection with respective segments of a video. The system further includes an analysis component configured to analyze the information and calculate user engagement scores for the respective video segments, wherein the user engagement scores reflect level of the plurality of users' interest regarding the respective video segments, and an identification component configured to identify a subset of the video segments associated with relatively higher user engagement scores in comparison to other video segments.

Abstract translation: 呈现了基于视频的相应段中的用户参与来分割视频的系统和方法。 在一个或多个方面，提供了一种系统，其包括接合部件，所述接合部件被配置为接收关于与视频的相应部分相关联的多个用户的相关联的信息。 该系统还包括一个分析部件，被配置为分析各个视频段的信息并计算用户参与度分数，其中用户参与度分数反映了多个用户对各个视频段的兴趣的水平，以及被配置为识别 与其他视频片段相比，与相对较高的用户参与度分数相关联的视频片段的子集。

公开(公告)号：US08856111B1

公开(公告)日：2014-10-07

申请号：US13914069

申请日：2013-06-10

Applicant: Google Inc.

Inventor： Daniel J. Clancy ,  Cristos J. Goodrow ,  Yu He ,  Kun Zhang

IPC: G06F17/30

CPC classification number: G06F17/3053 ,  G06F17/30029 ,  H04N21/252 ,  H04N21/4782

Abstract: Recommendations for a media item associated with a primary entity are based on co-interaction information gathered from other media content items of several different media types that are also associated with the primary entity. Co-interaction information can include, for example, co-click data for websites, co-watch data for videos, or co-purchase data for purchases. The co-interaction data is processed to determine a co-interaction score between primary media items and secondary media items. From the co-interaction scores, secondary entities associated with the secondary media items are determined. A relatedness score is determined for these secondary entities based on the aggregation of the co-interaction scores of the secondary media items they are associated with. The relatedness score indicates a determination of how related one entity is to another. The secondary entities are ranked according to relatedness score in order to determine secondary entities most relevant to the primary entity.

Abstract translation: 与主要实体相关联的媒体项目的建议基于从也与主要实体相关联的若干不同媒体类型的其他媒体内容项目收集的共同交互信息。 共同互动信息可以包括例如用于网站的共同点击数据，共同观看视频数据或共同购买用于购买的数据。 处理共同交互数据以确定主要媒体项目和次要媒体项目之间的共同交互评分。 从共同互动评分中确定与次要媒体项目相关联的辅助实体。 基于与它们相关联的二级媒体项目的共同交互得分的聚合，确定这些次级实体的相关性得分。 相关性分数表示确定一个实体与另一个实体的关联。 次要实体根据相关性得分进行排名，以确定与主要实体最相关的次级实体。