US 12,341,832 B2
Automatic adaptive digital content generation for collaborative documents using machine-learning-based digital content processing techniques
Navneet Kumar, Sydney (AU)
Assigned to ATLASSIAN PTY, LTD., Sydney (AU); and ATLASSIAN US, INC., San Francisco, CA (US)
Filed by ATLASSIAN PTY LTD., Sydney (AU); and ATLASSIAN US, INC., San Francisco, CA (US)
Filed on Dec. 29, 2022, as Appl. No. 18/147,871.
Prior Publication US 2024/0223628 A1, Jul. 4, 2024
Int. Cl. H04L 65/401 (2022.01)
CPC H04L 65/4015 (2013.01) 20 Claims
OG exemplary drawing
 
1. An apparatus for automatically generating adaptive digital content for a collaborative document, the apparatus comprising a display, at least one processor, and at least one memory including program code, the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least:
receive user input data associated with the collaborative document, wherein the user input data is generated by a client computing device associated with a user profile identifier, and wherein the user profile identifier is associated with a user profile stored in a data repository related to a document collaboration platform;
generate, via the document collaboration platform, one or more temporally correlated user input step events based on the user input data;
render, on one or more interactive user interfaces associated with the collaborative document, temporally sequenced digital content generated based on the one or more temporally correlated user input step events, wherein the temporally sequenced digital content can be associated with the user profile identifier;
generate suggested adaptive digital content based on model output generated by an adaptive digital content processing model comprised in a document assistance system, wherein the model output is generated based on at least a portion of the temporally sequenced digital content; and
render, on the one or more interactive user interfaces associated with the collaborative document, the suggested adaptive digital content.