US 12,406,517 B2
Systems and methods for providing a self-learning estimation advisor
Abhijit Kumar, Bangalore (IN); Arvind Maheswaran, Bangalore (IN); Amartya Ray, Thane (IN); Jenoy Easow, Bangalore (IN); and Glanda Meera Nazareth, Bangalore (IN)
Assigned to ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed by ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed on Feb. 17, 2023, as Appl. No. 18/110,951.
Prior Publication US 2024/0282135 A1, Aug. 22, 2024
Int. Cl. G06V 30/416 (2022.01); G06V 30/19 (2022.01)
CPC G06V 30/416 (2022.01) [G06V 30/1916 (2022.01); G06V 30/19193 (2022.01)] 18 Claims
OG exemplary drawing
 
1. A system, comprising:
a processor; and
a memory coupled to the processor, wherein the memory comprises processor-executable instructions, which on execution, cause the processor to:
receive, from a user interacting with the system, a first document and a second document, wherein an actual value is associated with the second document;
determine a set of variables for each of the first document and the second document, wherein the set of variables are determined based on a statistical analysis of historical data;
segregate the set of variables into a first set of variables corresponding to a categorical variables and a second set of variables corresponding to numerical variables, wherein the categorical variables are converted into binary codes using an encoding technique, and wherein the numerical variables are normalized using a normalization technique;
train, using a transformation module, an artificial neural network (ANN) model by performing linear transformation on the numerical variables, wherein the ANN model references a deep learning method including algorithms based on brain function, wherein the ANN model provides a relationship between inputs and outputs to discover a new pattern of the set of variables;
estimate, using the trained ANN model, a cost associated with each of the first document and the second document based on the segregated set of variables, wherein the cost associated with the first document comprises an estimated freight cost for the first document, and wherein the cost associated with the second document comprises an estimated true value for the second document; and
provide the estimated cost associated with the first document and the second document associated with the second document to the user, via a user interface, interacting with the system.