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公开(公告)号：US11144954B1
公开(公告)日：2021-10-12
申请号：US15880078
申请日：2018-01-25
Applicant: Facebook, Inc.
Inventor： Liang Xu , Chaochao Cai , Qing Li , Goran Predovic
Abstract: An online system promotes physical store visits by presenting users with content items for a physical store location and subsequently logs visits of online system users to the physical store location to track performance of a campaign associated with the presented content item. The online system registers attention events associated with the presented content items presented to users on third party publishing sites via tracking pixels and registers attention events as store front visit conversion events if, within a predetermined period of time from a valid attention event, a user has subsequently gone in and visited the physical store front location.
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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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公开(公告)号：US10922335B1
公开(公告)日：2021-02-16
申请号：US15883036
申请日：2018-01-29
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Goran Predovic , Liang Xu , Qing Li , Logan Michael Gore
Abstract: A method for providing content items to one or more client devices associated with at least one unresolved identifier. An unresolved identifier defines a context in which a client device accesses one or more online systems, the context not determined to be associated with a specific user. The method comprises identifying a set of unresolved identifiers, and identifying information describing one or more access events associated with each unresolved identifier. For each pair of unresolved identifiers, a similarity score for the pair is determined based on the identified information. Responsive to the similarity score exceeding a threshold similarity score, the pair of unresolved identifiers is clustered, the clustering indicating a prediction that the pair of unresolved identifiers are associated with a common user. Based on this clustering, a content item is displayed on or more user devices associated with at least one unresolved identifier of the set of unresolved identifiers.
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公开(公告)号：US10387715B1
公开(公告)日：2019-08-20
申请号：US16201852
申请日：2018-11-27
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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公开(公告)号：US10311244B2
公开(公告)日：2019-06-04
申请号：US15282693
申请日：2016-09-30
Applicant: Facebook, Inc.
Inventor： Weidong Wang , Erjie Ang , Yongfeng Liu , Liang Xu , Chaochao Cai
Abstract: An online system maintains characteristics for its users and may access characteristics of users maintained by a third party system. The online system may select content for a user of the third party system based on characteristics maintained by the third party system. If the third party system does not maintain a characteristic for its users, the generates a model predicting the characteristic for third party system users based on a set of online system users identified based on characteristics of third party system users. The online system clusters third party system users based on the predicted characteristic for other third party system users connected to the third party system user. Using verified characteristics for third party system users from a trusted third party system, the online system determines an accuracy of the predicted characteristic for third party system users in a cluster.
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Patent Agency Ranking
公开(公告)号：US11140188B1
公开(公告)日：2021-10-05
申请号：US16829511
申请日：2020-03-25
Applicant: Facebook, Inc.
Inventor： Tobias Henry Wooldridge , Chaochao Cai
Abstract: An online system determines the likelihood of an interaction between a user and a content item being an invalid interaction. The online system receives an indication of an interaction of a client device with a content item. The online system identifies a device ID for the client device and determines whether the device ID is associated with one or more browser IDs. If the device ID is not associated with any browser ID, the received interaction is likely an invalid interaction. The online system may further determine the likelihood of an online publisher manufacturing interactions. The online system determines a number of invalid interactions and a number of valid interactions associated with the online publisher. The online system determines a ratio between the number of invalid and valid interactions. If the ratio is larger than a threshold value, the online system determines that the online publisher is likely manufacturing interactions.
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公开(公告)号：US10803094B1
公开(公告)日：2020-10-13
申请号：US15883028
申请日：2018-01-29
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Goran Predovic
IPC: G06F16/00 , G06F16/28 , G06F16/955
Abstract: A method for determining reach of a content item that is displayed on one or more client devices associated with at least one unresolved identifier. An unresolved identifier defines a context in which a client device accesses one or more online systems, the context not determined to be associated with a specific user. The method comprises identifying a set of unresolved identifiers, and identifying information describing one or more access events associated with each unresolved identifier. For each pair of unresolved identifiers, a similarity score for the pair is determined based on the identified information. Responsive to the similarity score exceeding a threshold similarity score, the pair of unresolved identifiers is clustered, the clustering indicating a prediction that the pair of unresolved identifiers are associated with a common user. Finally, for the reach of the displayed content item is determined based on the clustering of the set of unresolved identifiers.
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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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公开(公告)号：US20180189676A1
公开(公告)日：2018-07-05
申请号：US15397530
申请日：2017-01-03
Applicant: Facebook, Inc.
Inventor： Goran Predovic , Chaochao Cai
CPC classification number: G06N20/00 , G06F16/00 , G06F16/9535 , G06Q10/10 , G06Q30/0241 , G06Q30/0251 , G06Q30/0269 , G06Q50/01
Abstract: Disclosed is an online system that infers interests of unresolved users for whom the interests are not known. The online system determines certain features about the unresolved users, but does not have certain information about the users themselves (e.g., their interests), so instead infers these attributes based on the features of the user. The online system provides the features as input to a classifier trained to predict a particular interest, and the classifier outputs a prediction of whether the user has the corresponding interest. In one embodiment, the online system trains a classifier for various interest values by forming training sets for the interests using the features for users who are logged into the online system and hence have known interests.
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公开(公告)号：US10832167B2
公开(公告)日：2020-11-10
申请号：US15397530
申请日：2017-01-03
Applicant: Facebook, Inc.
Inventor： Goran Predovic , Chaochao Cai
IPC: G06K9/62 , G06Q30/02 , G06K9/00 , H04N21/25 , G06F17/00 , G06N20/00 , G06Q50/00 , G06Q10/10 , G06F16/00 , G06F16/9535
Abstract: Disclosed is an online system that infers interests of unresolved users for whom the interests are not known. The online system determines certain features about the unresolved users, but does not have certain information about the users themselves (e.g., their interests), so instead infers these attributes based on the features of the user. The online system provides the features as input to a classifier trained to predict a particular interest, and the classifier outputs a prediction of whether the user has the corresponding interest. In one embodiment, the online system trains a classifier for various interest values by forming training sets for the interests using the features for users who are logged into the online system and hence have known interests.
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