公开(公告)号：US11947896B2

公开(公告)日：2024-04-02

申请号：US17848795

申请日：2022-06-24

Applicant: Adobe Inc.

Inventor： Peter Evan O'Donovan ,  Siddartha Reddy Turpu ,  Razvan Cotlarciuc ,  Oliver Markus Michael Brdiczka ,  Nipun Jindal ,  Costin-Stefan Ion

IPC: G06F40/109 ,  G06F16/583 ,  G06F40/126 ,  G06V30/413

CPC classification number: G06F40/109 ,  G06F16/5846 ,  G06F40/126 ,  G06V30/413

Abstract: Font recommendation techniques are described that provide recommendations of fonts based on a variety of factors, automatically and without user intervention in real time. This is performable in a variety of ways by addressing a wide range of considerations as part of machine learning, examples of which include context, popularity, similarity, customization, and topic compatibility.

公开(公告)号：US20230419014A1

公开(公告)日：2023-12-28

申请号：US17848795

申请日：2022-06-24

Applicant: Adobe Inc.

Inventor： Peter Evan O'Donovan ,  Siddartha Reddy Turpu ,  Razvan Cotlarciuc ,  Oliver Markus Michael Brdiczka ,  Nipun Jindal ,  Costin-Stefan Ion

IPC: G06F40/109 ,  G06F40/126 ,  G06V30/413 ,  G06F16/583

CPC classification number: G06F40/109 ,  G06F16/5846 ,  G06V30/413 ,  G06F40/126

Abstract: Font recommendation techniques are described that provide recommendations of fonts based on a variety of factors, automatically and without user intervention in real time. This is performable in a variety of ways by addressing a wide range of considerations as part of machine learning, examples of which include context, popularity, similarity, customization, and topic compatibility.

公开(公告)号：US20230419015A1

公开(公告)日：2023-12-28

申请号：US17849271

申请日：2022-06-24

Applicant: Adobe Inc.

Inventor： Peter Evan O'Donovan ,  Siddartha Reddy Turpu ,  Razvan Cotlarciuc ,  Oliver Markus Michael Brdiczka ,  Nipun Jindal ,  Costin-Stefan Ion

IPC: G06F40/109 ,  G06F40/211 ,  G06F40/186

CPC classification number: G06F40/109 ,  G06F40/211 ,  G06F40/186

Abstract: Font recommendation techniques are described that provide recommendations of fonts based on a variety of factors, automatically and without user intervention in real time. This is performable in a variety of ways by addressing a wide range of considerations as part of machine learning, examples of which include context, popularity, similarity, customization, and topic compatibility.

公开(公告)号：US11307881B1

公开(公告)日：2022-04-19

申请号：US17095290

申请日：2020-11-11

Applicant: Adobe Inc.

Inventor： Ripul Bhutani ,  Oliver Markus Michael Brdiczka ,  Doo Soon Kim ,  Aliakbar Darabi ,  Yinglan Ma

IPC: G06F3/0482 ,  G06F9/451 ,  G06N5/02 ,  G06F16/23

Abstract: In implementations of systems for generating suggestions with knowledge graph embedding vectors, a computing device implements a suggestion system to receive input data describing user interactions with an application for editing digital content. The suggestion system generates input embedding vectors based on the user interactions with the application and determines an item based on the input embedding vectors and knowledge graph embedding vectors generated from nodes of a knowledge graph describing a tutorial for editing digital content. The suggestion system generates an indication of the item for display in a user interface of a display device.