Publication Type : Conference Paper
Publisher : IEEE
Source : 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS)
Url : https://doi.org/10.1109/icicnis64247.2024.10823187
Campus : Chennai
School : School of Computing
Department : Computer Science and Engineering
Year : 2024
Abstract : In today's world, a lot people are searching and applying for jobs. When there is a need for company to recruit new employees, it is difficult for them to select the correct resume according to their job description from the lakhs of resume that they received. This project will help the recruiters to select the accurate resume with relevance to their job description. It will produce resumes which matches the best with the recruiter's job description by matching the skills, experience of resume with the job description. Used various advanced natural language processing models and deep learning models to provide more accurate results than any other existing models. With these methods the model achieved accuracy of 98%. Also, system will send mail to those people whose resume has not matched much with the job description stating the reason like what lacks in their resume when compared with job description. This will be helpful for candidates to know what lacks in them. Also, for the HR, interview questions will be generated according to each candidate resume. This will reduce the Reduce HR's work for preparing interview questions for each person.
Cite this Research Publication : R Ramyar, Gundapaneni Nagarani, S Natarajan, Deep Learning based Approach to Streamline Resume Categorization and Ranking, 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS), IEEE, 2024, https://doi.org/10.1109/icicnis64247.2024.10823187