US 12,008,600 B2
Sentiments based transaction systems and methods
Patrick Soon-Shiong, Los Angeles, CA (US)
Assigned to Nant Holdings IP, LLC, Culver City, CA (US)
Filed by Nant Holdings IP, LLC, Culver City, CA (US)
Filed on Nov. 30, 2022, as Appl. No. 18/072,671.
Application 18/072,671 is a continuation of application No. 17/860,462, filed on Jul. 8, 2022, granted, now 11,538,068.
Application 17/860,462 is a continuation of application No. 17/061,443, filed on Oct. 1, 2020, granted, now 11,430,014, issued on Aug. 30, 2022.
Application 17/061,443 is a continuation of application No. 16/566,712, filed on Sep. 10, 2019, granted, now 10,846,753, issued on Nov. 24, 2020.
Application 16/566,712 is a continuation of application No. 14/596,090, filed on Jan. 13, 2015, granted, now 10,453,097, issued on Oct. 22, 2019.
Claims priority of provisional application 61/926,512, filed on Jan. 13, 2014.
Prior Publication US 2023/0088997 A1, Mar. 23, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/02 (2023.01); G06Q 30/0251 (2023.01)
CPC G06Q 30/0269 (2013.01) 22 Claims
OG exemplary drawing
 
1. A digital sentiment analysis system comprising:
at least one computer readable memory storing software instructions; and
at least one processor coupled with the computer readable memory and wherein the processor, upon execution of the software instructions, performs operations to:
obtain, via a digital sensor, sensor data of an environment, wherein the sensor data comprises at least one digital data modality and at least some data derived by executing a recognition algorithm, wherein the recognition algorithm comprises at least one of the following recognition algorithms: a scale-invariant feature transform (SIFT) algorithm, a Fast Retina Key-point (FREAK) algorithm, a DAISY descriptor algorithm, or a Features from Accelerated Segment Test (FAST) algorithm;
associate one or more sentiment characteristics with at least some of the sensor data, wherein the associating the one or more sentiment characteristics comprises mapping a threshold number or percentage of items present in the sensor data to a sentiment characteristic;
generate one or more digital models of sentiment states in the environment based on at least some of the sensor data and the one or more sentiment characteristics;
determine a set of sentiment states relevant to the environment from the one or more digital models of sentiment states; and
facilitate a mobile device to take action based on the set of sentiment states relevant to the environment.