Engineering a Novel Recruitment System Using Gradient Boosted Decision Tree Algorithm and Business Intelligence Principles

Abstract

Using Business Intelligence to strategize the use of technology and reduce the rate of an Indian economic issue of unemployment by developing a Start-up web application using By coordinating with the Indian Sports and Cultural Institutions, and establishing agreements with NGOs/Corporates and other sponsorship providers to raise stipends/employment for underprivileged Indian youth using a novel algorithm with the GBDT algorithm for a suitable and secure recruiter recommendation system using firebase encryption. Since the Indian youth require a vast stage of opportunities and growth in variety of employment, the creatives and the sports industry are primarily focused to display limelight on those nurtured with inborn talents using our recruiter recommendation system using the 3 BI principles namely relevance, query intelligence and personalization. This app will seek to eradicate insufficient assessments, location barriers, inaccessibility of academies due to lack of funds, inadequate cultural categories, loopholes in the database due to weak security, and manual screening and verification of UUP details, this paper aims to give an overview and a studied literature review including proposed concepts and describes the need, significance and goal of developing an algorithm using business intelligence and machine learning to solve a socio-economic crisis.