Career Link – Online Job Posting & Recruitment Management System

The Career Link – Online Job Posting & Recruitment Management System provides a centralized web-based solution for addressing the major challenges associated with traditional recruitment processes. The proposed system integrates important recruitment activities such as job posting, job searching, resume uploading, online applications, candidate shortlisting, application tracking, interview scheduling, notifications, and administrative management within a single platform.   The system provides separate functionalities for Job Seekers, Employers, and Administrators, allowing each user to perform their respective activities efficiently. Employers can manage vacancies and applications, while job seekers can search for suitable opportunities, apply online, and monitor their application status. The administrator can manage users, monitor job postings, and maintain overall system operations.   The proposed methodology combines secure authentication, resume validation, keyword- and filter-based searching, candidate matching, and database management to improve the efficiency of recruitment activities. The system is evaluated using parameters such as response time, matching accuracy, search efficiency, usability, reliability, application processing time, user satisfaction, and security.   Overall, Career Link aims to reduce manual effort, paperwork, recruitment delays, and communication gaps while improving transparency and accessibility. The proposed system demonstrates how web-based technologies can be effectively applied to create a more organized, secure, and efficient recruitment environment. Future enhancements such as advanced AI-based matching, intelligent recommendations, stronger verification, and additional integrations can further improve the capabilities of the system.

[1]              A. B. Holm, “E-Recruitment: Towards an Ubiquitous Recruitment Process and Candidate  Relationship Management,” German Journal of Human Resource Management, vol. 26, no. 3, pp. 241–259, 10.1177/239700221202600302. Available: https://doi.org/10.1177/239700221202600302   [2]            S. Alamro, H. Dogan, D. Cetinkaya, N. Jiang, and K. Phalp, “Conceptualising and Modelling E-Recruitment Process for Enterprises through a Problem-Oriented Approach,” Information, vol. 9, no. 11, Art. no. 269, 2018. doi: 10.3390/info9110269. Available: https://www.mdpi.com/2078-2489/9/11/269   [3]            M. Maree, A. B. Kmail, and M. Belkhatir, “Analysis and Shortcomings of ERecruitment Systems: Towards a Semantics-Based Approach Addressing Knowledge Incompleteness and Limited Domain Coverage,” Journal of Information Science, vol. 45, no. 6, pp. 713–735, 2019. doi: 10.1177/0165551518811449. Available: https://doi.org/10.1177/0165551518811449   [4]             S. Khanvilkar, S. Shetty, D. Solanki, and S. Davare, “Smart Recruitment System,” International Journal of Computer Sciences and Engineering, vol. 7, no. 4, pp. 823–828, 2019. Available: https://www.ijcseonline.org/full_paper_view.php?paper_id=4124   [5]            W. Krugell et al., “Unveiling the Mysteries of the ‘Black Hole’ in Recruiting Systems: Connecting Recruiters and Job Seekers Like a Jigsaw Puzzle,” Procedia Manufacturing, vol. 3, pp. 3470–3477, 2015. doi: 10.1016/ j.promfg.2015.07.652. Available: https://doi.org/10.1016/j.promfg.2015.07.652   [6]             P. Gupta, P. Gupta, and S. Kumar, “Topic Modeling Driven Content Based Jobs Recommendation Engine for Recruitment Industry,” Procedia Computer Science, vol. 122, pp. 865–872, 2017. doi: 10.1016/ j.procs.2017.11.448. Available: https://doi.org/10.1016/j.procs.2017.11.448