Template-Type: ReDIF-Article 1.0
Author-Name: Meghana Atmakuri 
Author-Email: 2200031084cseh@gmail.com
Author-Name: Kanthi Rekha Tanari
Author-Email: 2200030305cseh@gmail.com
Author-Name: Balabadra Navya Sri
Author-Email: 2200030371cseh@gmail.com
Author-Name: M Kavitha
Author-Email: mkavita@kluniversity.in
Author-Name: Dharmaiah Devarapalli
Author-Email: drdharmaiah@kluniversity.in
Author-Name: M Kalyani
Author-Email: kalyani_m@pace.ac.in
Author-Name: D Mythrayee 
Author-Email: mythra2325@gmail.com
Title: Edu Scan: Optimizing talent discovery and streamlining hiring practices using AI
Abstract: Edu Scan is a machine learning-driven resume parser designed to analyse student resumes and predict their alignment with a benchmark document. The benchmark is created by aggregating key features and skills from resumes of students who have secured high-paying placements across various reputed universities. By utilizing Natural Language Processing mechanism, Edu Scan compares student resumes against this benchmark to assess familiarity and relevance. The system evaluates keyword matches, generates an accuracy score for each resume, and provides tailored suggestions for improvement. This innovative AI tool aims to optimize talent discovery by helping students align their resumes with industry standards, while assisting recruiters in streamlining the hiring process by identifying top candidates more efficiently.
Keywords: Artificial Intelligence, Education, Machine Learning, Natural Language Processing
Journal: Edu - Tech Enterprise
Pages: 19
Volume: 2
Issue: 
Year: 2024
Subtitle : 
File-URL: https://ete.sciten.org/index.php/ete/article/view/19/34
File-Format: application/pdf
Handle: RePEc:cua:edutec:v:2:y:2024:i::p:19:id:19