Hyperautomation in Super Shop Using Machine Learning †

Abstract

The purpose of this research was to determine how we can optimize both customer and seller experiences in a super shop using hyperautomation technology. Here, a smart bot was employed to speed up responses of simple consumer queries by utilizing natural language processing in real time. We also used machine learning frameworks, such as XGBoost, linear regression, random forest, and hybrid models together, to predict future product demand. In addition, data mining methods, such as the Apriori algorithm, FP growth algorithm, and GSP algorithm, were used to find out which algorithm can be used to determine the right way to place a product to increase the super shop sale.