公开(公告)号：US20160026918A1

公开(公告)日：2016-01-28

申请号：US14444477

申请日：2014-07-28

Applicant: YAHOO! INC.

Inventor： Nicola Barbieri ,  Francesco Bonchi ,  Giuseppe Manco

IPC: G06N5/04 ,  H04L29/08 ,  G06N99/00 ,  G06F17/30 ,  G06N7/00

CPC classification number: H04L67/22 ,  G06F17/30867 ,  G06N99/005 ,  G06Q30/0277 ,  G06Q30/0631 ,  G06Q50/01

Abstract: Provided herein is a system or method for a users-to-follow recommendation engine for, based at least in part on social network information and information about users in one or more social networks, determining features relating to users, including topical features and social features, determining, using a model constructed utilizing the determined features, for a set or users, a subset of the set of users for which the user has a high linkage, relative to other linkages in the set, and determining, using the model, and displaying to the user, a recommendation to follow and an associated explanation, of at least one particular user of the subset of the users wherein the associated explanation includes a topical-based explanation when a predominant basis for the high linkage is determined to be topical and a social-based explanation when a predominant basis for the high linkage is determined to be social.

Abstract translation: 本文提供了用于至少部分地基于社交网络信息和关于一个或多个社交网络中的用户的信息的用户跟随推荐引擎的系统或方法，确定与用户相关的特征，包括主题特征和社交特征 使用所确定的特征构建的模型，针对集合或用户，相对于该集合中的其他链接，用户具有高链接的用户集合的子集，以及使用模型确定，以及 向用户显示所述用户子集中的至少一个特定用户的关注建议和相关说明，其中相关联的解释包括基于主题的解释，当高联系的主要依据被确定为主题时， 当高度联系的主要依据被确定为社会时，就是以社会为基础的解释。

公开(公告)号：US20150019474A1

公开(公告)日：2015-01-15

申请号：US13938718

申请日：2013-07-10

Applicant: Yahoo! Inc.

Inventor： Nicola Barbieri ,  Francesco Bonchi

IPC: G06N5/02

CPC classification number: G06Q30/0201 ,  G06N7/005 ,  G06Q30/0251 ,  G06Q30/0276 ,  G06Q50/01

Abstract: The disclosure includes use of a feature-aware propagation model to identify one or more features of a product and one or more person(s), or members of a social network, to target, or user, for marketing the product having the identified features. The one or more person(s) identified using the model may be the person(s), or member(s), of a social network determined to have a maximum capability, relative to other members of the social network, for influencing the members of the social network in adopting, e.g., purchasing, a product having the identified features. In addition, parameters of the model may be determined using information about the social network, user preferences, and the products and features of the products.

Abstract translation: 本公开包括使用特征感知传播模型来识别产品和一个或多个个人或社会网络的成员的目标或用户的一个或多个特征，用于营销具有所识别的特征的产品 。 使用该模型识别的一个或多个人可以是被确定具有相对于社交网络的其他成员的最大能力的社会网络的个人或成员，以影响成员 的社会网络采用例如购买具有识别特征的产品。 此外，可以使用关于社交网络，用户偏好以及产品的产品和特征的信息来确定模型的参数。

公开(公告)号：US20170154356A1

公开(公告)日：2017-06-01

申请号：US14954118

申请日：2015-11-30

Applicant: Yahoo! Inc.

Inventor： Michele Trevisiol ,  Gabriele Tolomei ,  Nicola Barbieri ,  Mounia Lalmas ,  Puneet Mohan Sangal ,  Fabrizio Silvestri

IPC: G06Q30/02

Abstract: An online advertising system receives an advertisement from an advertiser. The system analyzes the advertisement, extracts its features and provides to the advertiser a quality rating for the advertisement which depends on a user engagement factor such as the predicted dwell time for the ad, given its features. The system further provides to the advertiser suggestions for improvements to the advertisement, such as a list of actionable guidelines that can improve the expected dwell time of the ad, and likely its conversion rate.

公开(公告)号：US20150347591A1

公开(公告)日：2015-12-03

申请号：US14294362

申请日：2014-06-03

Applicant: YAHOO! INC.

Inventor： Eric Bax ,  Jitesh Mehta ,  Nicola Barbieri ,  David Garcia Soriano

IPC: G06F17/30 ,  G06Q50/00 ,  G06Q30/02

CPC classification number: G06Q50/01 ,  G06F17/18 ,  G06Q30/0269

Abstract: Disclosed herein is a matching of multiple different social graphs to generate a combined social graph. Such a combined social graph may be searched and used in determining information to provide to a user, for example. An iterative metric learning approach may be used in matching multiple different social graphs. A mechanism is provided to validate a match from different social graphs. Match validation of data field matching is provided.

Abstract translation: 这里公开了多个不同社交图的匹配以生成组合的社交图。 例如，这样的组合社交图可以被搜索并用于确定提供给用户的信息。 可以使用迭代度量学习方法来匹配多个不同的社交图。 提供了一种机制来验证来自不同社交图表的匹配。 提供数据字段匹配的匹配验证。

公开(公告)号：US20150134402A1

公开(公告)日：2015-05-14

申请号：US14076551

申请日：2013-11-11

Applicant: Yahoo! Inc.

Inventor： Nicola Barbieri ,  Francesco Bonchi ,  Giuseppe Manco

IPC: G06Q50/00 ,  G06Q30/02

CPC classification number: G06Q50/01 ,  G06Q30/0201

Abstract: Disclosed is a system and method for detecting online social communities through network-oblivious community detection techniques that involve modeling social contagion from a log of user activity. The log includes a dataset of tuples that record the instances when a user has adopted an item at a specific time. The disclose systems and methods then apply a stochastic framework that assumes that the adoptions of the item are governed by an underlying diffusion process over an unobserved social network, and that such diffusion model is based on community-level influence. By fitting the model parameters to the user activity log, community membership information and level of influence information can be derived for each user in each community.

Abstract translation: 公开了一种通过网络遗忘社区检测技术来检测在线社区的系统和方法，其涉及从用户活动日志中建模社会传染病。 该日志包括用户在特定时间采用项目时记录实例的元组数据集。 公开的系统和方法然后应用一个随机框架，假设项目的采用受到一个不可观察的社会网络的潜在扩散过程的控制，而这种扩散模型是基于社区层面的影响。 通过将模型参数拟合到用户活动日志中，可以为每个社区中的每个用户导出社区成员信息和影响级别信息。

公开(公告)号：US20140337356A1

公开(公告)日：2014-11-13

申请号：US13889866

申请日：2013-05-08

Applicant: Yahoo! Inc.

Inventor： Nicola Barbieri ,  Francesco Bonchi ,  Giuseppe Manco

IPC: G06F17/30

CPC classification number: G06Q50/01

Abstract: Methods and systems for identifying communities based on information propagation data are described. One of the methods includes receiving a social graph, which includes nodes and relationships between the nodes. The method further includes receiving a number of the communities to find within the social graph, receiving data regarding propagation of information between the nodes, and calculating a probability of formation of a link between a first one of the nodes and a second one of the nodes based on the data. The link provides a direction of flow of media between the first and second nodes. The method includes calculating a probability that media will be accessed by the second node based on the data. One of the communities includes the first node, the second node, and the link.

Abstract translation: 描述了基于信息传播数据识别社区的方法和系统。 其中一种方法包括接收包括节点和节点之间的关系的社交图。 该方法还包括接收在社交图中找到的多个社区，接收关于节点之间的信息传播的数据，以及计算形成第一节点与第二节点之间的链接的概率 基于数据。 该链路提供第一和第二节点之间的介质流动方向。 该方法包括基于该数据来计算媒体将被第二节点访问的概率。 其中一个社区包括第一个节点，第二个节点和链接。

公开(公告)号：US20160187151A1

公开(公告)日：2016-06-30

申请号：US14586540

申请日：2014-12-30

Applicant: Yahoo! Inc.

Inventor： Nicola Barbieri ,  Daniele Quercia

IPC: G01C21/34 ,  G01C21/36 ,  G06F17/30

CPC classification number: G01C21/3446 ,  G01C21/20 ,  G01C21/3679

Abstract: Methods and/or systems are provided that may be utilized to recommend a contextual walking route for a number of venues, for example.

Abstract translation: 提供的方法和/或系统可用于为例如多个场所推荐上下文的步行路线。

公开(公告)号：US09342854B2

公开(公告)日：2016-05-17

申请号：US13889866

申请日：2013-05-08

Applicant: Yahoo! Inc.

Inventor： Nicola Barbieri ,  Francesco Bonchi ,  Giuseppe Manco

IPC: G06F17/30 ,  G06Q50/00

CPC classification number: G06Q50/01

Abstract: Methods and systems for identifying communities based on information propagation data are described. One of the methods includes receiving a social graph, which includes nodes and relationships between the nodes. The method further includes receiving a number of the communities to find within the social graph, receiving data regarding propagation of information between the nodes, and calculating a probability of formation of a link between a first one of the nodes and a second one of the nodes based on the data. The link provides a direction of flow of media between the first and second nodes. The method includes calculating a probability that media will be accessed by the second node based on the data. One of the communities includes the first node, the second node, and the link.

Abstract translation: 描述了基于信息传播数据识别社区的方法和系统。 其中一种方法包括接收包括节点和节点之间的关系的社交图。 该方法还包括接收在社交图中找到的多个社区，接收关于节点之间的信息传播的数据，以及计算形成第一节点与第二节点之间的链接的概率 基于数据。 该链路提供第一和第二节点之间的介质流动方向。 该方法包括基于该数据来计算媒体将被第二节点访问的概率。 其中一个社区包括第一个节点，第二个节点和链接。