US 11,886,824 B2
Sentiment progression analysis
Ninad D. Sathaye, Bangalore (IN); Raghav Bali, Bangalore (IN); Piyush Gupta, Bangalore (IN); and Krishnamohan Nandiraju, Hyderabad (IN)
Assigned to Optum Technology, Inc., Eden Prairie, MN (US)
Filed by Optum Technology, Inc., Eden Prairie, MN (US)
Filed on Jan. 28, 2022, as Appl. No. 17/586,972.
Application 17/586,972 is a continuation of application No. 16/902,936, filed on Jun. 16, 2020, granted, now 11,256,874.
Prior Publication US 2022/0164543 A1, May 26, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/35 (2020.01); H04M 3/51 (2006.01); G06Q 30/0241 (2023.01)
CPC G06F 40/35 (2020.01) [H04M 3/5141 (2013.01); H04M 3/5191 (2013.01); G06Q 30/0241 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
identifying, by one or more processors, a conversation block within a conversation data object;
identifying, by the one or more processors, an initial sentiment score for the conversation block;
identifying, by the one or more processors, a subjectivity probability value for the conversation block that describes an inferred likelihood that the conversation block is characterized by one or more subjective sentiments;
generating, by the one or more processors and a stage-wise penalty factor determination model, a stage-wise penalty factor for the conversation block that describes a stage-aware sentiment score for the conversation block based at least in part on a related conversation stage of a plurality of conversation stages associated with the conversation data object;
generating, by the one or more processors, and based at least in part on the initial sentiment score, the subjectivity probability value, and the stage-wise penalty factor, a regularized sentiment score for the conversation block; and
causing, by the one or more processors, one or more actions to be performed based at least in part on the regularized sentiment score.