CH. Rajya Lakshmi, Dr. M Uttam , B. Thrinath Chowdary, B. Trisha Tarini, CH. AnilKumar
Abstract
The rapid growth of digital hiring platforms has transformed the recruitment process, yet many students still face challenges in connecting with the right opportunities due to lack of guidance, limited industry exposure, and ineffective filtering of job roles. Traditional job portals often fail to provide personalized recommendations and meaningful networking opportunities, especially for fresh graduates. This project proposes an AI-enabled job recruitment platform integrated with alumni collaboration to bridge the gap between students, alumni, and recruiters. The system leverages Artificial Intelligence (AI) and Machine Learning (ML) techniques to match candidates with suitable job opportunities based on their skills, academic background, and career preferences. The platform uses Natural Language Processing (NLP) to analyze resumes and job descriptions, extracting relevant features such as skills, experience, and keywords. A recommendation engine built using Collaborative Filtering and Content-Based Filtering suggests jobs that best fit the candidate’s profile. Additionally, recruiters can efficiently filter candidates using AI-based ranking systems.
1.The study presented an efficient and user-friendly approach for developing an Online Job Portal System with Alumni Chapters, which integrates job recruitment functionalities with alumni networking features. 2.The proposed system combines job portal functionalities with alumni interaction, enabling students to not only search and apply for jobs but also connect with alumni for guidance, mentorship, and referrals. This integration enhances the overall effectiveness of the platform. 3.The system provides personalized job recommendations based on user skills, preferences, and profiles. This improves the relevance of job listings and increases the chances of successful placement compared to traditional job portals. 4.The inclusion of alumni chapters significantly improves user engagement. Students can interact with alumni, seek career advice, and gain insights into industry requirements, making the platform more interactive and beneficial. 5.The system demonstrated reliable performance with quick response times and accurate results. All modules such as user registration, job posting, job application, and alumni communication functioned smoothly and efficiently. 6.By providing a centralized platform for job listings, applications, and alumni networking, the system simplifies the job search process for students and fresh graduates. 7.The system can be effectively used by educational institutions, universities, and organizations to improve placement activities. It serves as a bridge between students, alumni, and recruiters, enhancing employment opportunities. 8.The system was thoroughly tested using various testing methods including unit testing, integration testing, functional testing, system testing, and acceptance testing. All test cases passed successfully, confirming that the system meets user requirements and performs reliably in real-world scenarios
References
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How to Cite This Paper
CH. Rajya Lakshmi, Dr. M Uttam , B. Thrinath Chowdary, B. Trisha Tarini, CH. AnilKumar (2026). AI-ENABLED JOB RECRUITMENT PLATFORM WITH ALUMNI COLLABORATION. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
