2026-11-03T23:09:58Z https://jmvra.org/oai.php

oai:jmvra.org:JMVRA2610006 2026-10-30 vol4

AI INTERNSHIP AGGREGATOR AND RECOMMENDATION PLATFORM ABISHECK M AKILESH V DHARANISH KUMAR M DHARSHAN A DHARUN M Artificial Intelligence Internship Aggregator Resume Analysis Skill Matching Internship Recommendation Application Tracking System Resume Parsing Job Matching Engineering, Science and Technology Students often find it difficult to discover suitable internships because opportunities are scattered across many company websites and job portals, and matching personal skills with the requirements of each role is largely a manual task. This paper presents an AI Internship Aggregator and Recommendation Platform that brings internship listings from multiple technology companies into a single web-based system. After login, a student uploads a resume in PDF, DOCX or text format. The system extracts the text, identifies technical skills, education, projects and experience using a JavaScriptbased natural language processing taxonomy, and calculates a skill match percentage between the student and every internship. Recommended companies are ranked by this score, and the matching and missing skills are displayed for each role. Students can save internships, view verified company details, apply, and monitor every opportunity through an Application Tracking System supported by an SQLite database. A profile module allows personal details, identified skills and the resume to be managed. By combining resume analysis with transparent skill matching, the proposed platform aims to reduce search effort, guide students towards relevant opportunities, and highlight the skills they should develop. JMVRA Publication 2026-10-30 Text Journal Article info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jmvra.org/viewpaperforall.php?paper=JMVRA2610006 https://jmvra.org/papers/JMVRA2610006.pdf Journal of Modern and Versatile Research Approach; ISSN 2984-8911; Vol. 4; Issue 10; pp. a75-a80 en https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Copyright © 2026 The Author(s). Published by JMVRA Publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).