AN INTELLECTUAL INFORMATION SYSTEM FOR RANK-BASED SELECTION OF WEB PROGRAMMERS

Abstract

The rapid growth of the digital economy and the increasing demand for high-quality web applications have intensified the need for skilled web programmers. The selection and evaluation of these professionals pose significant challenges, particularly for organizations seeking to balance technical proficiency, team collaboration, and alignment with project objectives. Traditional hiring methods often fail to address the complexities of evaluating candidates' multifaceted skills, leading to inefficiencies in recruitment processes and suboptimal project outcomes. As a result, the development of intellectual information systems for automated and objective evaluation of web programmers has emerged as a crucial area of study.

This article presents the conceptual framework of an intellectual information system for rank-based selection of web programmers. The proposed system integrates principles of artificial intelligence, machine learning, and multi-criteria decision analysis to ensure objective, transparent, and efficient evaluations. The core of the system is a multi-dimensional model that assesses candidates based on technical expertise, problem-solving skills, programming efficiency, adherence to coding standards, and soft skills such as communication and adaptability. A critical component of the system is its ability to dynamically weigh these criteria based on the specific requirements of a given role or project.

The primary goal of this research is to design a system that facilitates rank-based selection through objective scoring mechanisms, enabling organizations to identify candidates best suited to their specific requirements. By employing advanced data analytics, the system is capable of generating detailed profiles for each candidate, offering insights into their technical and behavioral competencies. Additionally, the system supports integration with corporate learning management systems (LMS) to provide targeted training recommendations for skill enhancement.

The intellectual information system proposed in this article represents a significant advancement in corporate IT education and human resource management. By automating and standardizing the evaluation process, the system not only reduces the time and cost associated with recruitment but also ensures a higher degree of precision in candidate selection. This innovation has the potential to transform the hiring landscape, fostering a more data-driven, equitable, and efficient approach to workforce development in the web programming industry.