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公开(公告)号:US12278832B2
公开(公告)日:2025-04-15
申请号:US17549193
申请日:2021-12-13
Applicant: Snap Inc.
Inventor: Neil Shah
IPC: G06F21/71 , H04L9/40 , G06F18/2411 , G06F21/00 , G06Q50/00
Abstract: Systems, devices, media and methods are presented for detecting anomalous resources and events in social data. The systems and methods receive a plurality of events associated with a plurality of resources, wherein the plurality of events includes a plurality of features. The systems and methods detect a set of anomalous resources from the plurality of resources and identify a set of anomalous events associated with the set of anomalous resources. The systems and methods cause an interface to be displayed on a computing device, wherein the interface includes the set of anomalous resources and the set of anomalous events.
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公开(公告)号:US12170683B2
公开(公告)日:2024-12-17
申请号:US18530502
申请日:2023-12-06
Applicant: Snap Inc.
Inventor: Neil Shah , Hamed Nilforoshan-Dardashti
IPC: H04L9/40 , G06F16/23 , G06F16/901
Abstract: Systems, devices, media, and methods are presented for determining a level of abusive network behavior suspicion for groups of entities and for identifying suspicious entity groups. A suspiciousness metric is developed and used to evaluate a multi-view graph across multiple views where entities are associated with nodes of the graph and attributes of the entities are associated with levels of the graph.
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公开(公告)号:US20240046674A1
公开(公告)日:2024-02-08
申请号:US18378245
申请日:2023-10-10
Applicant: Snap Inc.
Inventor: Vítor Silva Sousa , Nils Murrugarra-Llerena , Leonardo Ribas Machado das Neves , Neil Shah
IPC: G06V20/70 , G06F16/58 , G06N3/08 , G06F18/214 , G06F18/2431
CPC classification number: G06V20/70 , G06F16/5866 , G06N3/08 , G06F18/214 , G06F18/2431 , G06N3/04
Abstract: A messaging system performs engagement analysis based on labels associated with content items produced by users of the messaging system. The messaging system is configured to process content items comprising images to identify elements in the images and determine labels for the images based on conditions indicating when to associate a label of the labels with an image of the images based on the elements in the image. The messaging system is further configured to associate the label with the content item, in response to determining to associate the label with the image, associating the label with the content item. The messaging system is further configured to determine engagement scores for the label based on interactions of users with the content items associated with label and adjust the engagement scores to determine trends in the labels to generate adjusted engagement scores.
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公开(公告)号:US11641368B1
公开(公告)日:2023-05-02
申请号:US16450463
申请日:2019-06-24
Applicant: Snap Inc.
Inventor: Neil Shah , Mingyi Zhao , Yu-Hsin Chen
Abstract: Systems and methods are disclosed for automatically predicting a risk score of a user login attempt by receiving a user login attempt and generating a login feature vector associated with the user login attempt. The systems and methods further train a machine learning technique to establish a relationship between the login feature vector and the risk score. The trained machine learning technique is applied to new user login attempts to predict a risk score associated with the login attempt and issue an authentication challenge to the user if the risk score exceeds a predetermined threshold value.
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公开(公告)号:US20230262082A1
公开(公告)日:2023-08-17
申请号:US18303807
申请日:2023-04-20
Applicant: Snap Inc.
Inventor: Neil Shah , Mingyi Zhao , Yu-Hsin Chen
CPC classification number: H04L63/1425 , G06N20/00 , H04L63/083 , H04L63/1433
Abstract: Systems and methods are disclosed for automatically predicting a risk score of a user login attempt by receiving a user login attempt and generating a login feature vector associated with the user login attempt. The systems and methods further train a machine learning technique to establish a relationship between the login feature vector and the risk score. The trained machine learning technique is applied to new user login attempts to predict a risk score associated with the login attempt and issue an authentication challenge to the user if the risk score exceeds a predetermined threshold value.
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公开(公告)号:US20220207080A1
公开(公告)日:2022-06-30
申请号:US17248400
申请日:2021-01-22
Applicant: Snap Inc.
Inventor: Vítor Silva Sousa , Nils Murrugarra-Llerena , Leonardo Ribas Machado das Neves , Neil Shah
Abstract: A messaging system performs engagement analysis based on labels associated with content items produced by users of the messaging system. The messaging system is configured to process content items comprising images to identify elements in the images and determine labels for the images based on conditions indicating when to associate a label of the labels with an image of the images based on the elements in the image. The messaging system is further configured to associate the label with the content item, in response to determining to associate the label with the image, associating the label with the content item. The messaging system is further configured to determine engagement scores for the label based on interactions of users with the content items associated with label and adjust the engagement scores to determine trends in the labels to generate adjusted engagement scores.
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公开(公告)号:US20240129328A1
公开(公告)日:2024-04-18
申请号:US18530502
申请日:2023-12-06
Applicant: Snap Inc.
Inventor: Neil Shah , Hamed Nilforoshan-Dardashti
IPC: H04L9/40 , G06F16/23 , G06F16/901
CPC classification number: H04L63/1425 , G06F16/2379 , G06F16/9024
Abstract: Systems, devices, media, and methods are presented for determining a level of abusive network behavior suspicion for groups of entities and for identifying suspicious entity groups. A suspiciousness metric is developed and used to evaluate a multi-view graph across multiple views where entities are associated with nodes of the graph and attributes of the entities are associated with levels of the graph.
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公开(公告)号:US11863575B2
公开(公告)日:2024-01-02
申请号:US17726435
申请日:2022-04-21
Applicant: Snap Inc.
Inventor: Neil Shah , Hamed Nilforoshan-Dardashti
IPC: H04L9/40 , G06F16/23 , G06F16/901
CPC classification number: H04L63/1425 , G06F16/2379 , G06F16/9024
Abstract: Systems, devices, media, and methods are presented for determining a level of abusive network behavior suspicion for groups of entities and for identifying suspicious entity groups. A suspiciousness metric is developed and used to evaluate a multi-view graph across multiple views where entities are associated with nodes of the graph and attributes of the entities are associated with levels of the graph.
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公开(公告)号:US11212303B1
公开(公告)日:2021-12-28
申请号:US16235990
申请日:2018-12-28
Applicant: Snap Inc.
Inventor: Neil Shah
Abstract: Systems, devices, media and methods are presented for detecting anomalous resources and events in social data. The systems and methods receive a plurality of events associated with a plurality of resources, wherein the plurality of events includes a plurality of features. The systems and methods detect a set of anomalous resources from the plurality of resources and identify a set of anomalous events associated with the set of anomalous resources. The systems and methods cause an interface to be displayed on a computing device, wherein the interface includes the set of anomalous resources and the set of anomalous events.
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公开(公告)号:US12088613B2
公开(公告)日:2024-09-10
申请号:US18303807
申请日:2023-04-20
Applicant: Snap Inc.
Inventor: Neil Shah , Mingyi Zhao , Yu-Hsin Chen
CPC classification number: H04L63/1425 , G06N20/00 , H04L63/083 , H04L63/1433
Abstract: Systems and methods are disclosed for automatically predicting a risk score of a user login attempt by receiving a user login attempt and generating a login feature vector associated with the user login attempt. The systems and methods further train a machine learning technique to establish a relationship between the login feature vector and the risk score. The trained machine learning technique is applied to new user login attempts to predict a risk score associated with the login attempt and issue an authentication challenge to the user if the risk score exceeds a predetermined threshold value.
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