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@article{174087,
        author = {Mukunda Rudrakar and Swakshan Tayade and Dhiraj Wankhede and Umar Khan and Prof Gajanan Gaikwad},
        title = {An Intelligent System for Automated Resume Screening and Resume Building Using NLP and Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3814-3823},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174087},
        abstract = {AI Resume Analyzer is an artificial intelligence-based system that analyzes candidates' CVs and makes recommendations to improve them. The system takes the candidate's resume as input and processes it using machine learning algorithms to identify opportunities for improvement. The main goal of the system is to help job seekers create resumes that will successfully pass the interview selection process. To extract useful information from a candidate's resume, the system uses various approaches such as natural language processing, text mining and sentiment analysis. Review the candidate's experience, skills, education, and achievements to get feedback to improve their resume. The algorithm also evaluates your resume's layout, language, and spelling to determine whether it meets industry standards. job seekers and recruiters can use the intelligent resume parser. Recruiters can use the system to quickly find the best candidates for a specific position, and job seekers can use it to create resumes that are more likely to pass the selection process at interviews. Job seekers can increase their chances of getting hired in a selected position by using a smart resume analyzer.},
        keywords = {Natural Language Processing (NLP), Resume Parser, Resume Analysis, Part-of-speech tagging, Named Entity Recognition (NER).},
        month = {March},
        }