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公开(公告)号：US10728225B1
公开(公告)日：2020-07-28
申请号：US16293654
申请日：2019-03-06
Applicant: Facebook, Inc.
Inventor： Li Zhou , William Bullock , Anh Phuong Bui
Abstract: Embodiments include one or more client devices accessible by users, an online system, and one or more partner systems such that the online system is able to identify a user of the online system across different devices and browsers based on the user activity that occurs external to the online system. A user performs user actions (e.g. purchase a product) on a web page of a partner system and may provide personally identifiable information (PII) to the partner system. The partner system provides the hashed PII and user actions performed by the user to the online system. The online system identifies a user profile on the online system by matching personal information in the user profile to the hashed PII. The online system generates a confidence score indicating a likelihood that the identified user of the online system is the individual that performed the external user action.
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公开(公告)号：US10691930B1
公开(公告)日：2020-06-23
申请号：US16506859
申请日：2019-07-09
Applicant: Facebook, Inc.
Inventor： Aleksey Sergeyevich Fadeev , Li Zhou , Yimin Song , Goran Predovic , Chaochao Cai , Liang Xu
Abstract: An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.
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13.发明授权公开(公告)号：US10430827B2
公开(公告)日：2019-10-01
申请号：US14461361
申请日：2014-08-15
Applicant: Facebook, Inc.
Inventor： Li Zhou , Ian K. Abernathy , Yunzhi Gao , Kosin Sutthimala
Abstract: An online system receives information describing a target group of online system users from a third party system and determines whether to store the information describing the target group. Online system users included in the target group are identified and scores are determined for each of the identified user. A score associated with a user represents the online system's effectiveness in targeting content to the user via targeting criteria maintained by the online system. Based on the scores, the online system determines a group score associated with the target group and stores the information describing the target group if the group score satisfies one or more criteria. If the information describing the target group is stored, the online system may determine whether to continue storing the information describing the target group based on revenue obtained by the online system from presenting content based on the target group.
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公开(公告)号：US10412076B2
公开(公告)日：2019-09-10
申请号：US15282666
申请日：2016-09-30
Applicant: Facebook, Inc.
Inventor： Mehul S. Parikh , Marc Christian Saba , Li Zhou , Yimin Song
IPC: H04L29/06
Abstract: An online system receives a variety of identifiers associated with a user of the online system and generates a federated list of identifiers for the user that includes each of the received identifiers. Identifiers may be browser identifiers, device identifiers, Internet protocol address, personally identifiable information, or a user identifier of a different online system. For each identifier in the federated list of identifiers, the online system generates metadata information such as a confidence score indicating a degree of certainty that the identifier can be used to accurately identify the user of the online system. The online system aggregates features associated with the identifiers in the federated list of identifiers to generate a comprehensive user profile of the user and uses the comprehensive user profile to better serve the user.
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公开(公告)号：US10402865B2
公开(公告)日：2019-09-03
申请号：US14586673
申请日：2014-12-30
Applicant: Facebook, Inc.
Inventor： Yunzhi Gao , Li Zhou , Ian K. Abernathy , Michael Phillip Salem
IPC: G06Q30/02
Abstract: An online system receives information describing a target group of online system users from a third party system and stores the information describing the target group. The online system subsequently uses the target group to select content for presentation to one or more users. For example, users included in the target group are identified as eligible to be presented with content items. Based on revenue obtained by the online system from presenting content based on the target group, the online system determines a monetization value for the target group. The online system determines whether to continue storing the information describing the target group based on the monetization value.
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Patent Agency Ranking
公开(公告)号：US20180332140A1
公开(公告)日：2018-11-15
申请号：US15592108
申请日：2017-05-10
Applicant: Facebook, Inc.
Inventor： William Bullock , Liang Xu , Li Zhou
CPC classification number: H04L67/327 , G06F17/277 , G06F17/30702 , G06K9/00677 , G06Q30/0269 , H04L67/306
Abstract: An online system predicts household features of a user, e.g., household size and demographic composition, based on image data of the user, e.g., profile photos, photos posted by the user and photos posted by other users socially connected with the user, and textual data in the user's profile that suggests relationships among individuals shown in the image data of the user. The online system applies one or more models trained using deep learning techniques to generate the predictions. For example, a trained image analysis model identifies each individual depicted in the photos of the user; a trained text analysis model derive household member relationship information from the user's profile data and tags associated with the photos. The online system uses the predictions to build more information about the user and his/her household in the online system, and provide improved and targeted content delivery to the user and the user's household.
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公开(公告)号：US20170213241A1
公开(公告)日：2017-07-27
申请号：US15007125
申请日：2016-01-26
Applicant: Facebook, Inc.
Inventor： Li Zhou , Goran Predovic , Ovidiu Popa , Vikram Mukunda Rao Tankasali , Liang Xu
CPC classification number: G06Q30/0246 , G06Q30/0201 , G06Q50/01
Abstract: An audience analysis system determines and predicts reach and frequency information of online users. The system receives real-time ad impression data from ad publishers or other data providers as well as report requests from advertisers asking for the reach and frequency information. The reach and frequency information of online users describes characteristics of online users that are reached by the advertisers. Matched users and unmatched users are identified via online cookies. Atomic data units are generated to allow feature computation and reach prediction for online users in a more efficient way. Machine learning models are trained to help predict the reach and frequency of unmatched users and to generate reports. The audience analysis system provides the advertisers with the generated reports, responding to the report requests.
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18.发明授权公开(公告)号：US11049032B2
公开(公告)日：2021-06-29
申请号：US15685121
申请日：2017-08-24
Applicant: Facebook, Inc.
Abstract: An online system maintains an identity graph having links between different types of user identifying information (e.g., email addresses, phone numbers, user identifiers) describing various users of the online system. Based on information received from various sources describing relationships between different types of user identifying information describing a user, the online system generates confidence values for each link between different types of user identifying information. In some embodiments, a confidence value accounts for an amount of time since information describing a relationship between different types of user identifying information was received from a source. If the confidence value of a link between different types of user identifying information equals or exceeds a threshold value, the online system determines the different types of user identifying information are correlated with each other, allowing the online system to correlate user identifying information without storing user identifying information received from sources.
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公开(公告)号：US10412134B2
公开(公告)日：2019-09-10
申请号：US15294621
申请日：2016-10-14
Applicant: Facebook, Inc.
Inventor： Li Zhou
IPC: H04L29/06 , H04N21/436 , H04N21/45 , H04N21/442 , H04L12/28 , H04L29/12 , H04L12/24
Abstract: An online system generates a household device-user graph, which links one or more household devices in a household with one or more users, each of whom having a user profile in the online system. The household device-user graph can be used for effective content delivery to users of the online system. The device-user graph generated by the online system describes connections between household device users and household devices in the target household and usage of the household devices by the household device users. Each household device user represented in the device-user graph is connected to one or more household devices represented in the device-user graph. The online system determines whether one or more household device users identified in the device-user graph are users of the online system, and updates the user profiles of the identified household device users in response to a determination that the identified household device users are users of the online system.
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公开(公告)号：US10242251B2
公开(公告)日：2019-03-26
申请号：US15497454
申请日：2017-04-26
Applicant: Facebook, Inc.
Inventor： Aleksey Sergeyevich Fadeev , Li Zhou , Yimin Song , Goran Predovic , Chaochao Cai , Liang Xu
Abstract: An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.
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