公开(公告)号：US20170147936A1

公开(公告)日：2017-05-25

申请号：US15406521

申请日：2017-01-13

Applicant: Facebook, Inc.

Inventor： Jonathan J. Gross ,  Yihua Liao ,  Joshua Luke Krivoshein ,  Monika Leigh Bickert ,  Eugene Zarakhovsky

IPC: G06N7/00 ,  G06N99/00 ,  H04L29/08

CPC classification number: G06N7/005 ,  G06N99/005 ,  G06Q30/0282 ,  G06Q50/01 ,  H04L67/22 ,  H04L67/306

Abstract: An online system extracts features from an application linked to the online system. The application is used by users of the online system and posts content to the online system. A trained model is applied to the extracted features to generate a quality score for the application. The trained model is trained using features extracted from a set of training applications and quality scores manually assigned to the training applications, wherein the manually assigned quality scores indicate whether each training application satisfies a set of criteria and the generated quality score represents a probability of the application satisfying the set of criteria. Based on the quality score, content provided by the application is ranked for presentation to a user of the online system in relation to other content of the online system. The online system presents the content provided by the application to the user according to the ranking.

公开(公告)号：US20160171385A1

公开(公告)日：2016-06-16

申请号：US14567901

申请日：2014-12-11

Applicant: Facebook, Inc.

Inventor： Jonathan J. Gross ,  Yihua Liao ,  Joshua Luke Krivoshein ,  Monika Leigh Bickert ,  Eugene Zarakhovsky

IPC: G06N99/00 ,  H04L29/08

CPC classification number: G06N7/005 ,  G06N99/005 ,  G06Q30/0282 ,  G06Q50/01 ,  H04L67/22 ,  H04L67/306

Abstract: An online system extracts features from an application linked to the online system. The application is used by users of the online system and posts content to the online system. A trained model is applied to the extracted features to generate a quality score for the application. The trained model is trained using features extracted from a set of training applications and quality scores manually assigned to the training applications, wherein the manually assigned quality scores indicate whether each training application satisfies a set of criteria and the generated quality score represents a probability of the application satisfying the set of criteria. Based on the quality score, content provided by the application is ranked for presentation to a user of the online system in relation to other content of the online system. The online system presents the content provided by the application to the user according to the ranking

Abstract translation: 在线系统从链接到在线系统的应用程序中提取功能。 该应用程序由在线系统的用户使用，并将内容发布到在线系统。 将经过训练的模型应用于提取的特征以产生应用的质量得分。 使用从一组训练应用提取的特征和手动分配给训练应用的质量得分来训练训练的模型，其中手动分配的质量分数指示每个训练应用是否满足一组标准，并且所生成的质量得分表示 应用程序满足一套标准。 基于质量得分，应用程序所提供的内容被排列为与在线系统的其他内容相关联地呈现给在线系统的用户。 在线系统根据排名将用户提供的内容呈现给用户

公开(公告)号：US11023923B2

公开(公告)日：2021-06-01

申请号：US14285289

申请日：2014-05-22

Applicant: Facebook, Inc.

Inventor： Vijaye Ganesh Raji ,  Jason Duane Clark ,  Eugene Zarakhovsky ,  Jonathan J. Gross ,  Brent Dorman

IPC: G06Q30/02 ,  G06F21/60 ,  G06F21/55

Abstract: Embodiments are disclosed for identifying a suspect application based on multiple operating factors from use of multiple applications. The embodiments can generate a representative distribution of a selected factor based on collected information corresponding to multiple operating factors from use of multiple applications. The embodiments can compare a representative distribution of a target factor with the representative distribution of the selected factor and identify a suspect application when these distributions are different.

公开(公告)号：US10083401B2

公开(公告)日：2018-09-25

申请号：US15406521

申请日：2017-01-13

Applicant: Facebook, Inc.

Inventor： Jonathan J. Gross ,  Yihua Liao ,  Joshua Luke Krivoshein ,  Monika Leigh Bickert ,  Eugene Zarakhovsky

IPC: G06N7/00 ,  H04L29/08 ,  G06Q50/00 ,  G06Q30/02 ,  G06N99/00

CPC classification number: G06N7/005 ,  G06N20/00 ,  G06Q30/0282 ,  G06Q50/01 ,  H04L67/22 ,  H04L67/306

Abstract: An online system extracts features from an application linked to the online system. The application is used by users of the online system and posts content to the online system. A trained model is applied to the extracted features to generate a quality score for the application. The trained model is trained using features extracted from a set of training applications and quality scores manually assigned to the training applications, wherein the manually assigned quality scores indicate whether each training application satisfies a set of criteria and the generated quality score represents a probability of the application satisfying the set of criteria. Based on the quality score, content provided by the application is ranked for presentation to a user of the online system in relation to other content of the online system. The online system presents the content provided by the application to the user according to the ranking.

公开(公告)号：US20150339705A1

公开(公告)日：2015-11-26

申请号：US14285289

申请日：2014-05-22

Applicant: Facebook, Inc.

Inventor： Vijaye Ganesh Raji ,  Jason Duane Clark ,  Eugene Zarakhovsky ,  Jonathan J. Gross ,  Brent Dorman

IPC: G06Q30/02 ,  G06F21/60

CPC classification number: G06Q30/0248 ,  G06F21/552 ,  G06F21/60 ,  G06Q30/02

Abstract: Embodiments are disclosed for identifying a suspect application based on multiple operating factors from use of multiple applications. The embodiments can generate a representative distribution of a selected factor based on collected information corresponding to multiple operating factors from use of multiple applications. The embodiments can compare a representative distribution of a target factor with the representative distribution of the selected factor and identify a suspect application when these distributions are different.

Abstract translation: 公开了用于基于来自多个应用的​​使用的多个操作因素识别可疑应用的实施例。 基于来自使用多个应用的​​多个操作因素的收集的信息，实施例可以生成所选因子的代表性分布。 实施例可以将目标因子的代表性分布与所选因子的代表性分布进行比较，并且当这些分布不同时识别可疑应用。