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@article{179316,
        author = {Kankanala Sahithi and Pinjari Sanjana and Sreeja Sumkara and Shyamala Akhil and Avinash Amaragani},
        title = {Resume Screening System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6574-6584},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179316},
        abstract = {The Resume Screening System is an
innovative, AI-powered tool that aims to speed up the
hiring process. Current resume screening process is
time taking and prone to human bias, particularly when
there are large number of applicants. This study focuses
on the issues of efficiently assessing, retrieving, and
evaluating important information from candidate
resumes. It compares the system will ensure that only
the most relevant profiles according to the job
requirements are shortlisted. Present screening systems
will only match exact keywords, our system
understands the meaning behind the words to match
candidates based on the context. The goal of this system
is to provide an accurate and time saving tool for the
recruiters that will improve decision-making during the
hiring process. The system can be integrated into
existing HR platforms or it can be utilized
independently by small and medium scale
organizations. In the end, this system will not only
reduce the manual workload but also improves the
quality of hiring by ensuring that best-fit candidates are
prioritized.},
        keywords = {Resume Screening, Semantic Matching, Candidate Shortlisting, Skill-Based Filtering, JobProfile Matching.},
        month = {May},
        }