The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 25, 2026
Filed:
Oct. 24, 2023
Adobe Inc., San Jose, CA (US);
University of Maryland, College Park, MD (US);
Puneet Mathur, College Park, MD (US);
Vlad Morariu, Potomac, MD (US);
Verena Kaynig-Fittkau, Cambridge, MA (US);
Jiuxiang Gu, College Park, MD (US);
Franck Dernoncourt, Seattle, WA (US);
Quan Tran, San Jose, CA (US);
Ani Nenkova, Philadelphia, PA (US);
Dinesh Manocha, College Park, MD (US);
Rajiv Jain, Falls Church, VA (US);
Adobe Inc., San Jose, CA (US);
University of Maryland, College Park, MD (US);
Abstract
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a temporal dependency graph. For example, the disclosed systems generate from a text document, a structural vector, a syntactic vector, and a semantic vector. In some embodiments, the disclosed systems generate a multi-dimensional vector by combining the various vectors. In these or other embodiments, the disclosed systems generate an initial dependency graph structure and an adjacency matrix utilizing an iterative deep graph learning model. Further, in some embodiments, the disclosed systems generate an entity-level relation matrix utilizing a convolutional graph neural network. Moreover, in some embodiments, the disclosed systems generate a temporal dependency graph from the entity-level relation matrix and the adjacency matrix.