公开(公告)号：US20190197069A1

公开(公告)日：2019-06-27

申请号：US14343931

申请日：2013-03-15

Applicant: Yahoo! Inc.

Inventor： Xin Fan ,  Todd Beaupre ,  Brian Webb

IPC: G06F16/9535 ,  G06Q50/00 ,  G06F16/435

CPC classification number: G06F16/9535 ,  G06F16/437 ,  G06Q50/01

Abstract: A method for content selection. The method comprises identifying a reference to content associated with a social media network user having a ranking above a pre-determined level, identifying one or more occurrences of the reference attributed to at least one additional social media network user, where the one or more occurrences are indicative of popularity of the content, and selecting the reference corresponding to the content based on the popularity.

公开(公告)号：US09424319B2

公开(公告)日：2016-08-23

申请号：US14344759

申请日：2013-03-15

Applicant: Yahoo! Inc.

Inventor： Xin Fan ,  Todd Beaupre ,  Jean-Marc Langlois

IPC: G06F17/30

CPC classification number: G06F17/3053 ,  G06F17/30 ,  G06F17/30867

Abstract: A method for selecting a social media network user. The method comprises obtaining one or more parameters indicative of quality of social media network content from the social media network user, ranking the social media network user based on the one or more parameters, and determining whether the social media network user is selected based on the ranking.

Abstract translation: 一种用于选择社交媒体网络用户的方法。 该方法包括从社交媒体网络用户获取指示社交媒体网络内容的质量的一个或多个参数，基于一个或多个参数对社交媒体网络用户进行排名，以及基于该社交媒体网络用户是否选择社交媒体网络用户 排行。

公开(公告)号：US20130132409A1

公开(公告)日：2013-05-23

申请号：US13738582

申请日：2013-01-10

Applicant: Yahoo! Inc.

Inventor： Todd Beaupre ,  James J. DeCarlo

IPC: G06F17/30

CPC classification number: G06F16/9535 ,  G06F16/41 ,  G06F16/437 ,  G06F16/48 ,  G06Q30/0603

Abstract: Methods and systems of providing media to a media consumer are disclosed herein. A media rating for at least one media item can be received from a consumer and stored on a consumer profile. Using a consumer interaction, the media consumer can request to import all available media having a consumer rating higher than a predetermined threshold to an online media library of the consumer. In another embodiment, using a consumer interaction, the media consumer can request to add to an online music library all media items associated with an artist, a genre, or other media item attribute.

Abstract translation: 本文公开了向媒体消费者提供媒体的方法和系统。 可以从消费者接收至少一个媒体项目的媒体评级，并存储在消费者资料中。 使用消费者交互，媒体消费者可以请求将具有高于预定阈值的消费者评级的所有可用媒体导入消费者的在线媒体库。 在另一个实施例中，使用消费者交互，媒体消费者可以请求向在线音乐库添加与艺术家，类型或其他媒体项目属性相关联的所有媒体项目。

公开(公告)号：US20150310018A1

公开(公告)日：2015-10-29

申请号：US14344759

申请日：2013-03-15

Applicant: YAHOO! INC

Inventor： Xin Fan ,  Todd Beaupre ,  Jean-Marc Langlois

IPC: G06F17/30

CPC classification number: G06F17/3053 ,  G06F17/30 ,  G06F17/30867

Abstract: A method for selecting a social media network user. The method comprises obtaining one or more parameters indicative of quality of social media network content from the social media network user, ranking the social media network user based on the one or more parameters, and determining whether the social media network user is selected based on the ranking.

Abstract translation: 一种用于选择社交媒体网络用户的方法。 该方法包括从社交媒体网络用户获取指示社交媒体网络内容的质量的一个或多个参数，基于一个或多个参数对社交媒体网络用户进行排名，以及基于该社交媒体网络用户是否选择社交媒体网络用户 排行。

公开(公告)号：US08909626B2

公开(公告)日：2014-12-09

申请号：US13660175

申请日：2012-10-25

Applicant: Yahoo! Inc.

Inventor： Seung-Taek Park ,  Wei Chu ,  Todd Beaupre ,  Deepak K. Agarwal ,  Scott Roy ,  Raghu Ramakrishnan

IPC: G06F17/30

CPC classification number: G06F17/30699

Abstract: A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined. Based on user features of a user and items a user has consumed, a set of nearest neighbor items are identified as a set of candidate items, and affinity scores of candidate items are determined. Based on the affinity scores, a candidate item from the set of candidate items is recommended to the user.

Abstract translation: 基于协同过滤技术来确定用于多个项目的项目项目亲和度的集合。 确定基于项目项目亲和度的集合的项目的最近邻居项目的集合。 基于最小二乘回归确定用于多个项目和一组用户特征的一组用户特征项目亲和度。 部分基于用户特征项亲属度的集合来确定一组用户特征的最近邻居项目。 确定每个项目和每个用户特征的最近邻项目的兼容关联权重。 基于用户的用户特征和用户消费的项目，将一组最近邻项目识别为一组候选项目，并确定候选项目的亲和度分数。 基于亲和度分数，向用户推荐来自候选项集合的候选项目。

公开(公告)号：US20130054593A1

公开(公告)日：2013-02-28

申请号：US13660175

申请日：2012-10-25

Applicant: Yahoo! Inc.

Inventor： Seung-Taek Park ,  Wei Chu ,  Todd Beaupre ,  Deepak K. Agarwal ,  Scott Roy ,  Raghu Ramakrishnan

IPC: G06F17/30

CPC classification number: G06F17/30699

Abstract: A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined. Based on user features of a user and items a user has consumed, a set of nearest neighbor items are identified as a set of candidate items, and affinity scores of candidate items are determined. Based on the affinity scores, a candidate item from the set of candidate items is recommended to the user.

Abstract translation: 基于协同过滤技术来确定用于多个项目的项目项目亲和度的集合。 确定基于项目项目亲和度的集合的项目的最近邻居项目的集合。 基于最小二乘回归确定用于多个项目和一组用户特征的一组用户特征项目亲和度。 部分基于用户特征项亲属度的集合来确定一组用户特征的最近邻居项目。 确定每个项目和每个用户特征的最近邻项目的兼容关联权重。 基于用户的用户特征和用户消费的项目，将一组最近邻项目识别为一组候选项目，并确定候选项目的亲和度分数。 基于亲和度分数，向用户推荐来自候选项集合的候选项目。