RecruitMatch (RM): An Intelligent Candidate Selection Algorithm for Modern Recruitment

Abstract

It is a challenge for recruiters in the current competitive job market to sift through a large number of applications against each of the vacancies available. This process may take a lot of time and in most cases, deserving candidates get turned away. To mitigate this challenge, we have created the RecruitMatch (RM) algorithm, which lets users select the candidates depending on the user information they have submitted. Using RM, recruiters are able to Search and Filter out the applicants by their qualification, experience, and competencies quickly. RM algorithm makes it easier for the recruiters to get the best candidates for a specific job which makes the hiring process more effective. Recruiters are able to make the best hiring sourcing decisions for their organisation as well as cut down on the time and costs involved.

Introduction

RecruitMatch (RM) addresses the growing complexity and inefficiency of the modern recruitment process, where a single job posting attracts overwhelming numbers of applicants, making it difficult and time-consuming for recruiters to find the best candidates quickly. This challenge is common not only in corporations but also in colleges and startup incubators, where matching talent with opportunities is critical.

The RM algorithm streamlines recruitment by centralizing candidate and employer data, allowing candidates to upload resumes and detailed profiles while enabling recruiters to efficiently filter, score, and shortlist applicants based on qualifications and experience. The system reduces manual screening by calculating match scores and sorting candidates by relevance and activity, facilitating faster and more accurate hiring decisions.

The platform uses a multi-tier architecture with cloud-hosted databases (MongoDB) and secure access controls for users and administrators. Recruiters can review shortlisted candidates and make final selections based on interview outcomes. The system also ensures secure user registration with email verification.

Drawing from existing research on competency mapping, web technologies, and user experience improvements, RecruitMatch leverages automation and efficient data filtering to enhance recruitment, particularly within educational and startup contexts. It reduces recruiter workload, speeds up hiring, and helps deserving candidates get noticed, all while maintaining data security and usability.

Conclusion

The RecruitMatch (RM) approach offers a high-performing platform which is simple and safe for use to solve the main problems faced by job finders, educational institutions, and startup incubators when in need of qualified people. Through improving how candidates apply for positions and how they get shortlisted, the RM algorithm helps organisations in seeking and placing the right talent faster for the right purpose. Our tool saves organisations from the challenge of dealing with the bulk of applications to find the most appropriate candidates that include time and resources. The system matches applicants with prospective positions accurately so as to improve the productivity and efficiency of the overall recruitment processes.

References

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Copyright

Copyright © 2025 Sahithi Venkata Pokuri, Samiksha Racha, Karishma M, Sruthi Sree N, Mamlesh VA, Karthikeyan D. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.