International Journal of Science, Engineering and TechnologyAuthors: Posipoyina Jaya Sree, Guna Tirumala Satish, Naimisa Bamala, Gokarakonda Leela Bhavani
Abstract: Organizations now find the hiring process to be inef- fective and time-consuming due to the sharp increase in job appli- cations. Conventional resume screening techniques mostly depend on human labor, keyword matching, and rudimentary Applicant Tracking Systems (ATS), which frequently fall short of capturing individuals’ actual potential and may introduce prejudice. This project suggests an Intelligent Resume AI-Powered Screening System that uses cutting-edge methods from Natural Language Processing and Artificial Intelligence to improve and automate the applicant screening process in order to address these issues. The suggested system uses NLP-based parsing algorithms to extract, evaluate, and interpret data from resumes. It finds important characteristics and transforms them into structured data, including abilities, education, experience, certificates, and projects. The necessary competences are extracted from job descriptions concurrently. The system uses vector representations and semantic analysis to compare resumes with job criteria using embedding techniques and similarity metrics like cosine similar- ity. In order to rank applicants according to their suitability for the position, the system also incorporates machine learning algorithms. Deep learning and transformer-based architectures are examples of advanced models that may be used to enhance contextual comprehension and lessen reliance on precise keyword matches. Additionally, the system has capabilities like suggestion creation, candidate classification (e.g., extremely appropriate, somewhat suitable, and not suitable), and automated scoring. By anonymizing sensitive information like name, gender, and location throughout the screening process, this initiative aims to reduce bias in hiring. This encourages impartial and equitable hiring practices. The system is also scalable and effective at managing high resume quantities, which makes it appropriate for real-world hiring situations. The suggested approach seeks to greatly shorten the time needed for recruiting, increase ap- plicant selection accuracy, and boost overall hiring effectiveness. Additionally, it lays the groundwork for upcoming improvements including integration with chatbot-based hiring platforms, real- time analytics, and adaptive learning models. Thus, in the age of digital transformation, the Intelligent Resume AI-Powered Screening System is a contemporary, effective, and equitable method of hiring.
