US 12,299,618 B2
Recommendations over meeting life cycle with user centric graphs and artificial intelligence
Vipindeep Vangala, Hyderabad (IN); Rajeev Gupta, Hyderabad (IN); Abhishek Arun, London (GB); Daniel Dechelotte, Houilles (FR); Sangita N. Pitre, Hyderabad (IN); Prakash Kumar Pandey, Bihar (IN); Grzegorz S. Kukla, Sliwice (PL); and Sarunas Marciuska, London (GB)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Jun. 30, 2022, as Appl. No. 17/854,247.
Prior Publication US 2024/0005244 A1, Jan. 4, 2024
Int. Cl. G06Q 10/00 (2023.01); G06Q 10/0633 (2023.01)
CPC G06Q 10/0633 (2013.01) 20 Claims
OG exemplary drawing
 
1. A system comprising:
at least one processor; and
memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
receiving a trigger related to an entity of interest;
identifying a user sub-graph on the entity of interest;
analyzing the user sub-graph by applying a first machine learning algorithm to the user sub-graph to identify a first set of a plurality of closely related entities;
re-analyzing the user sub-graph by applying a second machine learning algorithm to the first set of a plurality of closely related entities to identify a second set of one or more other closely related entities, the second set of closely related entities being a subset of the first set of closely related entities identified by the first machine learning algorithm, wherein the second machine learning algorithm is different from the first machine learning algorithm, and an output of the second machine learning algorithm including the second set of one or more closely related entities is applied as feedback to update the first machine learning algorithm to refine the first set of a plurality of closely related entities;
generating an insight based on the second set of one or more closely related entities; and
causing to display the insight on a graphical user interface.