US 11,055,668 B2
Machine-learning-based application for improving digital content delivery
Hongche Liu, Fremont, CA (US); Divya Venugopalan, Redwood City, CA (US); and Shaunak Chatterjee, Sunnyvale, CA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Jun. 26, 2018, as Appl. No. 16/19,359.
Prior Publication US 2019/0392396 A1, Dec. 26, 2019
Int. Cl. G06Q 10/10 (2012.01); G06N 20/00 (2019.01); G06F 16/901 (2019.01)
CPC G06Q 10/1053 (2013.01) [G06F 16/9024 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
generating a personalized conversation graph associated with a user identifier, the personalized conversation graph representing a conversational flow for sequenced deliverable digital content to a client device associated with the user identifier, the personalized conversation graph including a plurality of nodes that represent a plurality of interactive dialogues for presenting to a user associated with the user identifier by a software application executing at a computer, the personalized conversation graph including one or more edges that connect the plurality of nodes, the one or more edges representing one or more transitions between the plurality of interactive dialogues, the generating of the personalized conversation graph being performed using one or more machine learning algorithms and one or more hardware processors;
based on a signal that indicates an online job-seeking activity and that is received from the client device, executing the software application to generate and cause display of a user interface on the client device, the user interface including a prompt related to job-seeking guidance for the user;
based on an indication of a first action, by the user, received from the client device in response to the prompt, selecting and processing a first node of the personalized conversation graph;
to cause display, in the user interface, of a first incentive content item associated with a first interactive dialogue represented by the first node of the personalized conversation graph, and a first call-to-action content item associated with the first incentive content item; and
in response to a further indication of a second action received from the client device in response to the first call-to action content item, selecting and processing a second node, connected via an edge to the first node, in the personalized conversation graph, to cause display, in the user interface, of a further incentive content item associated with a further interactive dialogue represented by the second node of the personalized conversation graph, and a further call-to-action content item associated with the further incentive content item.