Refining Element Associations for Form Structure Extraction

    公开(公告)号:US20230134460A1

    公开(公告)日:2023-05-04

    申请号:US17517434

    申请日:2021-11-02

    Applicant: Adobe Inc.

    Abstract: In implementations of refining element associations for form structure extraction, a computing device implements a structure system to receive estimate data describing estimated associations of elements included in a form and a digital image depicting the form. An image patch is extracted from the digital image, and the image patch depicts a pair of elements of the elements included in the form. The structure system encodes an indication of whether the pair of elements have an association of the estimated associations. An indication is generated that the pair of elements have a particular association based at least partially on the encoded indication, bounding boxes of the pair of elements, and text depicted in the image patch.

    Customer journey management using machine learning

    公开(公告)号:US12205127B2

    公开(公告)日:2025-01-21

    申请号:US17232591

    申请日:2021-04-16

    Applicant: ADOBE INC.

    Abstract: Interactions between a user and an e-commerce platform are automatically guided to increase the chances of a conversion. Previous sequences of interactions (e.g., conversion journeys and non-conversion journeys) with the e-commerce platform are collected, an artificial neural network (ANN) learns how to estimate a safety value a current user state by learning from previous user interactions (e.g., conversion and non-conversion journeys), a software agent of the e-commerce platform applies a current user state of the user to the ANN to determine a current safety value, and the software agent provides content to the user based on the current safety value and the current user state.

    CUSTOMER JOURNEY MANAGEMENT USING MACHINE LEARNING

    公开(公告)号:US20220335508A1

    公开(公告)日:2022-10-20

    申请号:US17232591

    申请日:2021-04-16

    Applicant: ADOBE INC.

    Abstract: Interactions between a user and an e-commerce platform are automatically guided to increase the chances of a conversion. Previous sequences of interactions (e.g., conversion journeys and non-conversion journeys) with the e-commerce platform are collected, an artificial neural network (ANN) learns how to estimate a safety value a current user state by learning from previous user interactions (e.g., conversion and non-conversion journeys), a software agent of the e-commerce platform applies a current user state of the user to the ANN to determine a current safety value, and the software agent provides content to the user based on the current safety value and the current user state.

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