OPPORTEXA - College Placement Tracking System

This research paper presents the design and development of an AI-integrated College Placement Tracking System aimed at simplifying and automating campus recruitment activities. The proposed system provides a centralized platform connecting students, companies, and placement officers. The system is developed using React for the frontend, Java Spring Boot for backend services, and MySQL for database management. It provides features such as student registration, profile management, resume uploading, job posting, eligibility checking, job applications, and application status tracking. Additionally, AI-based features such as Resume Analysis, Skill Gap Analysis, and Interview Preparation are incorporated to support students in identifying skill requirements and improving their placement readiness. The proposed system aims to reduce manual work, improve communication, enhance recruitment transparency, and make the campus placement process more efficient and accessible.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-06
DOI
https://doi.org/10.5281/zenodo.24012652
Primary Topic
AI and HR Technologies
Type
preprint
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preprint

OPPORTEXA - College Placement Tracking System

BHARGAVI KKANDUKURI, Priyanka k, TANUJA KOLANAKUDURU, SAI PRUDHVI RAJ NAIDU THOTA
2 links
Zenodo (CERN European Organization for Nuclear Research)
AI and HR Technologies
preprint

OPPORTEXA - College Placement Tracking System

BHARGAVI KKANDUKURI, Priyanka k, TANUJA KOLANAKUDURU, SAI PRUDHVI RAJ NAIDU THOTA
preprint en

Abstract

This research paper presents the design and development of an AI-integrated College Placement Tracking System aimed at simplifying and automating campus recruitment activities. The proposed system provides a centralized platform connecting students, companies, and placement officers. The system is developed using React for the frontend, Java Spring Boot for backend services, and MySQL for database management. It provides features such as student registration, profile management, resume uploading, job posting, eligibility checking, job applications, and application status tracking. Additionally, AI-based features such as Resume Analysis, Skill Gap Analysis, and Interview Preparation are incorporated to support students in identifying skill requirements and improving their placement readiness. The proposed system aims to reduce manual work, improve communication, enhance recruitment transparency, and make the campus placement process more efficient and accessible.

Zenodo (CERN European Organization for Nuclear Research)
AI and HR Technologies
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