公开(公告)号：US20160179968A1

公开(公告)日：2016-06-23

申请号：US14579710

申请日：2014-12-22

Applicant: Facebook, Inc.

Inventor： Holly Marie Ormseth ,  Elad Gerson ,  Guy Dassa ,  Khalid Bakry El-Arini ,  Gaurav Shankar ,  Yuanxuan Wang ,  Varun Kacholia ,  Prasoon Mishra ,  David Vickrey ,  Sanjeet Uday Hajarnis ,  Sahil P. Thaker

IPC: G06F17/30

CPC classification number: G06F17/30867

Abstract: Systems, methods, and non-transitory computer readable media configured to detect access by a user to an original content item relating to a story. At least one of a comments based technique, a token based technique, and a tag based technique is performed on content items. Constraints are applied to identify at least one follow up content item from the content items relating to a development of the story.

Abstract translation: 被配置为检测用户对与故事相关的原始内容项的访问的系统，方法和非暂时计算机可读介质。 对内容项目执行基于注释的技术，基于令牌的技术和基于标签的技术中的至少一个。 应用限制来从与故事发展相关的内容项目中识别至少一个后续内容项目。

公开(公告)号：US09286575B2

公开(公告)日：2016-03-15

申请号：US14286803

申请日：2014-05-23

Applicant: Facebook, Inc.

Inventor： Max Gubin ,  Wayne Kao ,  David Vickrey ,  Alexey Maykov

IPC: G06N99/00 ,  G06Q10/06 ,  G06Q50/00 ,  G06F17/30

CPC classification number: G06N99/005 ,  G06F17/30867 ,  G06Q10/06393 ,  G06Q50/01

Abstract: Machine learning models are used for ranking news feed stories presented to users of a social networking system. The social networking system divides its users into different sets, for example, based on demographic characteristics of the users and generates one model for each set of users. The models are periodically retrained. The news feed ranking model may rank news feeds for a user based on information describing other users connected to the user in the social networking system. Information describing other users connected to the user includes interactions of the other users with objects associated with news feed stories. These interactions include commenting on a news feed story, liking a news feed story, or retrieving information, for example, images, videos associated with a news feed story.

Abstract translation: 机器学习模型用于对社交网络系统的用户提供新闻馈送故事。 社交网络系统将用户分为不同的集合，例如基于用户的人口特征，并为每组用户生成一个模型。 这些模型定期进行再培训。 新闻排序模型可以基于描述在社交网络系统中连接到用户的其他用户的信息来为用户排序新闻馈送。 描述连接到用户的其他用户的信息包括其他用户与与新闻馈送故事相关联的对象的交互。 这些互动包括评论新闻Feed故事，喜欢新闻Feed故事或检索信息，例如图像，与新闻Feed故事相关的视频。

公开(公告)号：US20140172875A1

公开(公告)日：2014-06-19

申请号：US13715999

申请日：2012-12-14

Applicant: Facebook, Inc.

Inventor： Dan Yigal Rubinstein ,  David Vickrey ,  Robert William Cathcart ,  Lars Seren Backstrom ,  Romain Jean Thibaux

IPC: G06F17/30

CPC classification number: G06F17/3053 ,  G06F17/24 ,  G06F17/30867 ,  G06Q50/01

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.

Abstract translation: 社交网络系统为用户生成访问社交网络系统的新闻源。 选择与社交网络系统的用户相关联的候选故事，并确定每个候选故事的预期值分数。 期望值分数基于用户对候选故事进行各种类型的交互的概率和每种类型的交互的数值。 互动类型的数值代表了交互类型的社交网络系统的价值。 根据预期值得分，候选人的故事排名，排名用于选择新闻源的候选故事。