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    Machine learning modeling using social graph signals
    11.
    发明授权
    Machine learning modeling using social graph signals 有权

    公开(公告)号：US11003997B1

    公开(公告)日：2021-05-11

    申请号：US15725075

    申请日：2017-10-04

    Applicant: Snap Inc.

    Inventor： John Cain Blackwood ,  Jason Brewer ,  Nima Khajehnouri ,  Hadi Minooei ,  Benjamin C. Steele ,  Qian You

    IPC: G06N5/02 ,  G06N20/00 ,  G06F16/951

    Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

    CHATBOT LONG-TERM MEMORY
    12.
    发明申请
    CHATBOT LONG-TERM MEMORY 有权

    公开(公告)号：US20240414108A1

    公开(公告)日：2024-12-12

    申请号：US18677723

    申请日：2024-05-29

    Applicant: Snap Inc.

    Inventor： Haowen Sun ,  William Spencer Mulligan ,  Nathan Kenneth Boyd ,  Hee Hun Kim ,  Dmytro Ishchenko ,  Lily Hinkeldey ,  Jason Brewer ,  Charles Melbye ,  Aleksandr Mashrabov

    IPC: H04L51/02 ,  G06F16/34 ,  H04L51/216

    Abstract: A chatbot system for an interactive platform is disclosed. The chatbot system retrieves a conversation history of one or more conversations between a user and a chatbot from a conversation history datastore and generates one or more summarized memories using the conversation history. One or more moderated memories are generated using the summarized memories. The moderated memories are stored in a memories datastore. A user prompt is received, and a current conversation context is generated from a current conversation between the user and the chatbot. One or more memories are retrieved from the memories datastore using the current conversation context. An augmented prompt is generated using the user prompt and the one or more memories, which is communicated to a generative AI model. A response is received from the generative AI model to the augmented prompt, which is provided to the user.

    PREDICTING A CONVERSION RATE
    13.
    发明申请
    PREDICTING A CONVERSION RATE 有权

    公开(公告)号：US20240378638A1

    公开(公告)日：2024-11-14

    申请号：US18315288

    申请日：2023-05-10

    Applicant: Snap Inc.

    Inventor： Weizhi Li ,  Vineet Abhishek ,  Jason Brewer ,  Roman Grachev ,  Yugi Deng ,  David B. Lue

    IPC: G06Q30/0242 ,  G06Q30/0241 ,  G06Q30/0273

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for predicting a conversion rate. The program and method provide for receiving, from an advertisement service, a bid to display a first advertisement at a computing device; determining, in response to receiving the bid, a set of features that relate to the first advertisement; providing the set of features to a machine learning model configured to output a predicted conversion rate for the first advertisement, the machine learning model having been trained based on multi-task learning using plural sets of features corresponding to plural second advertisements, the plural sets of features being associated with both click-through conversions and view-through conversions; and determining, based on the output of the machine learning model with respect to the set of features, the predicted conversion rate for the first advertisement.

    MACHINE LEARNING MODELING USING SOCIAL GRAPH SIGNALS
    14.
    发明申请
    MACHINE LEARNING MODELING USING SOCIAL GRAPH SIGNALS 有权

    公开(公告)号：US20210224661A1

    公开(公告)日：2021-07-22

    申请号：US17225767

    申请日：2021-04-08

    Applicant: Snap Inc.

    Inventor： John Cain Blackwood ,  Jason Brewer ,  Nima Khajehnouri ,  Hadi Minooei ,  Benjamin C. Steele ,  Qian You

    IPC: G06N5/02 ,  G06F16/951 ,  G06N20/00

    Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

    Machine learning modeling using social graph signals
    16.
    发明授权
    Machine learning modeling using social graph signals 有权

    公开(公告)号：US11966853B2

    公开(公告)日：2024-04-23

    申请号：US17225767

    申请日：2021-04-08

    Applicant: Snap Inc.

    Inventor： John Cain Blackwood ,  Jason Brewer ,  Nima Khajehnouri ,  Hadi Minooei ,  Benjamin C. Steele ,  Qian You

    IPC: G06N5/02 ,  G06F16/951 ,  G06N5/022 ,  G06N20/00

    CPC classification number: G06N5/022 ,  G06F16/951 ,  G06N20/00

    Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

    Systems, devices, and methods for content selection
    18.
    发明授权
    Systems, devices, and methods for content selection 有权

    公开(公告)号：US11204949B1

    公开(公告)日：2021-12-21

    申请号：US16049318

    申请日：2018-07-30

    Applicant: Snap Inc.

    Inventor： Jason Brewer ,  Rodrigo B. Farnham ,  Nima Khajehnouri ,  David B. Lue ,  Zhuo Xu

    IPC: G06F16/31 ,  G06Q50/00 ,  G06F17/18 ,  G06F16/335

    Abstract: Disclosed are systems, methods, and computer-readable storage media to present content on an electronic display. In one aspect, a method includes identifying a first candidate content and a second candidate content for presentation on an electronic display, determining a first probability and a second probability that the first candidate content and the second candidate content respectively will elicit a particular type of input response, determining a first weight and a second weight based on the first probability and the second probability respectively, selecting either the first content or the second content based on the first weight and the second weight; and presenting the selected content on the electronic display.

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