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公开(公告)号：US10360466B2
公开(公告)日：2019-07-23
申请号：US15391735
申请日：2016-12-27
Applicant: Facebook, Inc.
Inventor： Shaomei Wu , Lada Ariana Adamic , Jeffrey C. Wieland , Omid Farivar , Hermes Germi Pique Corchs , Matt King , Brett Alden Lavalla , Balamanohar Paluri
Abstract: Systems, methods, and non-transitory computer-readable media can receive an image. One or more concepts depicted in the image are identified based on machine learning techniques. The one or more concepts are filtered based on filtering criteria to identify one or more selected concepts. An image description is generated comprising the one or more selected concepts.
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公开(公告)号：US10127316B2
公开(公告)日：2018-11-13
申请号：US14455798
申请日：2014-08-08
Applicant: Facebook, Inc.
Inventor： Russell Lee-Goldman , Lada Ariana Adamic , David M. Goldblatt , Yuval Kesten , Mark Andrew Rich , Nidhi Gupta , Amy Campbell , Andrew Rocco Tresolini Fiore
Abstract: In one embodiment, a method includes receiving unstructured text from a user of a social-networking system, determining whether the unstructured text includes a request for a recommendation, identifying one or more first entity names in the unstructured text, generating a structured query based upon the one or more first entity names, identifying, in the social graph, one or more second entity names corresponding to the structured query, and presenting the one or more second entity names and the unstructured text in a social context of the user. The unstructured text may include text of a post or message generated by the user on a social-networking system. A score may be generated based on the unstructured text to determine whether the text includes a request for recommendation using a machine-learning model based on comparison of the unstructured text to the one or more predetermined words associated with requests for recommendation.
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公开(公告)号：US20180181832A1
公开(公告)日：2018-06-28
申请号：US15391735
申请日：2016-12-27
Applicant: Facebook, Inc.
Inventor： Shaomei Wu , Lada Ariana Adamic , Jeffrey C. Wieland , Omid Farivar , Hermes Germi Pique Corchs , Matt King , Brett Alden Lavalla , Balamanohar Paluri
CPC classification number: G06K9/2063 , G06F16/583 , G06K9/00288 , G06K9/18 , G06K2209/01 , G06N20/00 , G06Q10/10 , G06Q30/00 , G06Q50/01
Abstract: Systems, methods, and non-transitory computer-readable media can receive an image. One or more concepts depicted in the image are identified based on machine learning techniques. The one or more concepts are filtered based on filtering criteria to identify one or more selected concepts. An image description is generated comprising the one or more selected concepts.
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公开(公告)号：US20210328950A1
公开(公告)日：2021-10-21
申请号：US17135756
申请日：2020-12-28
Applicant: Facebook, Inc.
Inventor： Ariel Benjamin Evnine , Lada Ariana Adamic , Peter Henry Martinazzi , Ojus Abhimanyu Patil
Abstract: The present disclosure relates to systems and methods for increasing messaging activity in a messaging system. Using the interactions of users with each other and/or with the messaging system, the disclosed systems and methods can predict how likely a pairing of two or more users are to engage in a highly active messaging thread. Based on this prediction, the disclosed methods and systems can, for example, more effectively organize contact lists and conduct promotional efforts associated with messaging features.
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公开(公告)号：US10152544B1
公开(公告)日：2018-12-11
申请号：US14841136
申请日：2015-08-31
Applicant: Facebook, Inc.
Inventor： Adrien Thomas Friggeri , Bogdan State , Lada Ariana Adamic , Erich James Owens
Abstract: Some embodiments include a method of detecting and analyzing virally propagating subject matter in a social networking system. The method includes processing user activities in the social networking system through a relevancy filter to identify a subset of user activities that are relevant to a viral propagation study. The social networking system can construct, in response to selecting a user activity as a graph exploration seed, a user activity cascade by exploring the social graph in the social networking system, starting from a social network node corresponding to the user activity. The user activity cascade can comprise social network nodes found during the graph exploration. The social networking system can determine that the user activity cascade is virally propagating based at least upon a total size of the user activity cascade.
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Patent Agency Ranking
公开(公告)号：US20170099240A1
公开(公告)日：2017-04-06
申请号：US14964232
申请日：2015-12-09
Applicant: Facebook, Inc.
Inventor： Ariel Benjamin Evnine , Lada Ariana Adamic , Peter Henry Martinazzi , Ojus Abhimanyu Patil
CPC classification number: H04L67/22 , G06Q10/0639 , G06Q50/01 , H04L51/046 , H04L51/16 , H04L51/24 , H04L51/32 , H04W4/21
Abstract: The present disclosure relates to systems and methods for increasing messaging activity in a messaging system. Using the interactions of users with each other and/or with the messaging system, the disclosed systems and methods can predict how likely a pairing of two or more users are to engage in a highly active messaging thread. Based on this prediction, the disclosed methods and systems can, for example, more effectively organize contact lists and conduct promotional efforts associated with messaging features.
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公开(公告)号：US10313280B2
公开(公告)日：2019-06-04
申请号：US14964232
申请日：2015-12-09
Applicant: Facebook, Inc.
Inventor： Ariel Benjamin Evnine , Lada Ariana Adamic , Peter Henry Martinazzi , Ojus Abhimanyu Patil
Abstract: The present disclosure relates to systems and methods for increasing messaging activity in a messaging system. Using the interactions of users with each other and/or with the messaging system, the disclosed systems and methods can predict how likely a pairing of two or more users are to engage in a highly active messaging thread. Based on this prediction, the disclosed methods and systems can, for example, more effectively organize contact lists and conduct promotional efforts associated with messaging features.
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公开(公告)号：US20190095544A1
公开(公告)日：2019-03-28
申请号：US15719236
申请日：2017-09-28
Applicant: Facebook, Inc.
Inventor： Bogdan State , Lada Ariana Adamic , Carlos Gomez Uribe
Abstract: Methods, systems, computer-readable media, and apparatuses for using, by one or more computer devices, engagement actions by users of a social network as behavioral signals for evaluating the quality of a content item shared by those users. Once the quality of a content item has been evaluated in this manner, an action can be performed on that content item (e.g., changing the visibility of that content item within the social network).
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公开(公告)号：US20180032898A1
公开(公告)日：2018-02-01
申请号：US15220733
申请日：2016-07-27
Applicant: Facebook, Inc.
Inventor： Shaomei Wu , Isabel Kloumann , Lada Ariana Adamic , Erich James Owens
Abstract: Systems, methods, and non-transitory computer-readable media can receive a plurality of comments to a posted content item. Each of the plurality of comments is associated with at least one category of a plurality of categories based on a machine learning model. A first comment of the plurality of comments is selected for inclusion in a comment sample to be presented in a graphical user interface based on the first comment being associated with a first category of the plurality of categories. A second comment of the plurality of comments is selected for inclusion in the comment sample based on the second comment being associated with a second category of the plurality of categories.
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公开(公告)号：US20160042069A1
公开(公告)日：2016-02-11
申请号：US14455798
申请日：2014-08-08
Applicant: FACEBOOK, INC.
Inventor： Russell Lee-Goldman , Lada Ariana Adamic , David M. Goldblatt , Yuval Kesten , Mark Andrew Rich , Nidhi Gupta , Amy Campbell , Andrew Rocco Tresolini Fiore
IPC: G06F17/30
CPC classification number: G06F17/30864 , G06F17/278 , G06F17/3043 , G06Q50/00
Abstract: In one embodiment, a method includes receiving unstructured text from a user of a social-networking system, determining whether the unstructured text includes a request for a recommendation, identifying one or more first entity names in the unstructured text, generating a structured query based upon the one or more first entity names, identifying, in the social graph, one or more second entity names corresponding to the structured query, and presenting the one or more second entity names and the unstructured text in a social context of the user. The unstructured text may include text of a post or message generated by the user on a social-networking system. A score may be generated based on the unstructured text to determine whether the text includes a request for recommendation using a machine-learning model based on comparison of the unstructured text to the one or more predetermined words associated with requests for recommendation.
Abstract translation: 在一个实施例中，一种方法包括从社交网络系统的用户接收非结构化文本，确定非结构化文本是否包括对推荐的请求，识别非结构化文本中的一个或多个第一实体名称，基于 所述一个或多个第一实体名称在所述社交图中标识与所述结构化查询相对应的一个或多个第二实体名称，以及在所述用户的社会环境中呈现所述一个或多个第二实体名称和所述非结构化文本。 非结构化文本可以包括用户在社交网络系统上生成的帖子或消息的文本。 可以基于非结构化文本来生成分数，以基于非结构化文本与与推荐请求相关联的一个或多个预定单词的比较来确定文本是否包括使用机器学习模型的推荐请求。
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