US 12,086,169 B2
Collaborative resolution framework
Dhilip Kumar, Bangalore (IN); Ponnayan Sekar, Attibee (IN); Hung Dinh, Austin, TX (US); and Bijan Kumar Mohanty, Austin, TX (US)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Mar. 31, 2022, as Appl. No. 17/657,442.
Prior Publication US 2023/0315764 A1, Oct. 5, 2023
Int. Cl. G06F 16/332 (2019.01); G06F 40/20 (2020.01); G06F 40/30 (2020.01); G06N 20/20 (2019.01)
CPC G06F 16/3329 (2019.01) [G06F 40/20 (2020.01); G06F 40/30 (2020.01); G06N 20/20 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
generating a conversation flow signature based on a set of communication transcripts, each of the communication transcripts being associated with a support request for a product, each of the communication transcripts being a text transcript of a communication between a respective customer and a respective customer support agent;
classifying the conversation flow signature into one of a plurality of categories, the conversation flow signature being classified by using a machine learning classifier that is trained based on customer support records, each of the plurality of categories corresponding to a respective set of steps for configuring or repairing the product; and
outputting an indication of the respective set of steps that is associated with the category in which the conversation flow signature is classified,
wherein the conversation flow signature encodes a graph having a first node that corresponds to a problem domain, a second node that corresponds to a behavior of the product, and at least one edge that leads into the second node, the edge being indicative of a potential cause of the behavior of the product.