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@article{204553,
        author = {Sakshi Priya and Siddhi Kumari},
        title = {Job Portal With Ai-Based Resume Matching},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {4140-4146},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204553},
        abstract = {The increase in number of job applications and the subjectivity of recruitment process inherent in manual hiring are tremendous drawbacks to the modern hiring systems which leads to inefficiency, unconscious discrimination, and poor candidate job fit. The research question is what is the effectiveness of an AI based job portal to automatize and optimize the process of screening candidates, parsing resumes and matching jobs, as well increasing the level of fairness and effectiveness in recruiting process. The suggested system, Smart Hire AI, uses the advanced techniques of Machine Learning (ML) and Natural Language Processing (NLP) to calculate the semantic similarity between resume and job description, extract the skills that are relevant, and prioritize the candidates, according to predetermine minimum skill-match threshold of 60%. The architecture to be used in the design of the system is a modular and scalable one, where MongoDB is used to provide a flexible and large volume data storage, Fast API to perform efficient processing and models integration on the backend, and React.js to provide an interactive and friendly user experience. The matching model based on the resume and similarity is designed using the vector-based representation of text and proximity points to guarantee objective and fact-driven recruiting suggestions.},
        keywords = {Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Resume Parsing, Automated Candidate Screening, Job Matching System.},
        month = {June},
        }