公开(公告)号：US20240403339A1

公开(公告)日：2024-12-05

申请号：US18328925

申请日：2023-06-05

Applicant: ADOBE INC.

Inventor： Vahid Azizi ,  Chun Hao Wang ,  Somdeb Sarkhel ,  Saayan Mitra ,  Richard Pong Nam Sinn

IPC: G06F16/33 ,  G06F40/205 ,  G06F40/30

Abstract: Systems and methods for generating contextual document embeddings and recommending similar articles based on the document embeddings are described. Embodiments are configured to receive a document query and encode a plurality of candidate sentences from a candidate document to obtain a plurality of contextual sentence embeddings. The contextual sentence embeddings each represent a semantic context of a corresponding sentence from the plurality of candidate sentences. Embodiments then generate a candidate document embedding by combining the plurality of contextual sentence embeddings and provide the candidate document in response to the document query based on the candidate document embedding.

公开(公告)号：US12061916B2

公开(公告)日：2024-08-13

申请号：US17657477

申请日：2022-03-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Thomas Donahue ,  Neha Gautam ,  Kyoung Tak Kim ,  Jakub Plichta ,  Keenan Villani-Holland ,  Gabriel Palma Coelho ,  Chun Hao Wang ,  Allan Young

IPC: G06F9/451

CPC classification number: G06F9/451

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.

公开(公告)号：US11809969B2

公开(公告)日：2023-11-07

申请号：US16916807

申请日：2020-06-30

Applicant: ADOBE INC.

Inventor： Richard Pong Nam Sinn ,  Chun Hao Wang ,  Thomas Todd Donahue

IPC: G06N20/00 ,  G06F16/9535 ,  G06F18/24

CPC classification number: G06N20/00 ,  G06F16/9535 ,  G06F18/24

Abstract: An improved analytics system dynamically generates, integrates, and deploys multiple models for use related to a particular user and/or user segment. The integrated model analytics system can deploy a set of models specifically identified for a user from a group of models related to the service. This set of models can be used to provide recommendations for the user related to content of the service. As the user continues to interact with the service, the integrated model analytics system can dynamically update multiple models from the set of models based on real-time user interactions. These updated models can be used to generate updated recommendations for the user that can be used to dynamically update content presented to the user. In addition, this updated model can be used when providing recommendations for users in other user segments.

公开(公告)号：US20230315491A1

公开(公告)日：2023-10-05

申请号：US17657477

申请日：2022-03-31

Applicant: Adobe Inc.

Inventor： Oliver Brdiczka ,  Thomas Donahue ,  Neha Gautam ,  Kyoung Tak Kim ,  Jakub Plichta ,  Keenan Villani-Holland ,  Gabriel Palma Coelho ,  Chun Hao Wang ,  Allan Young

IPC: G06F9/451

CPC classification number: G06F9/451

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.