International Journal of Science, Engineering and TechnologyAuthors: Mr.Rajeshirke Satej Mahendra, Ms. Rajguru Jaya Mahendra, Mr.Sambherao Eshwar Mahadeo, Prof. V. A. Karad, Prof. S. B. Bhosale, Prof. A. P. Bangar, Dr. A. A. Khatri
Abstract: Traditional job portals rely on keyword matching, not allowing semantics of skills. Thus, they fail to connect candidates with jobs. Cursory manual resume screening takes 30-40 seconds. Conventional online assessments lack any integrity. DreamRole, an AI-based career recommendation and recruitment software which alleviates these essential limitations is presented in the paper. DreamRole uses Natural Language Processing (NLP) to parse resumes in PDF, DOC, DOCX, and TXT formats. It extracts skills, experience and education from a database of 200 technical skills. A matching algorithm based on the content generates a weighted relevance score that takes into consideration your skills (70%), experience (20%) and education (10%). It recommends only those positions that achieve a minimum threshold of 50 percent. The Semantic Skill Variation mapping helps in eliminating false negatives. By using OpenCV for real-time proctoring, the platform detects face abnormality, mobile phone presence, tab switching, forbidden key-stroke and terminates the test automatically on 3 successive occurrences of the same behaviour. A web speech API based hands-free navigation voice assistant (English, Hindi, Marathi) using a multilingual. Bulk resume processing can allow up to 10000 candidates in a single batch with automatic account generation feature and CSV credential download. The evaluation shows that we achieve an F1-score of 94.7% for parsing resumes, NDCG@10 of 0.79(27.4% improvement over the keyword baseline), proctoring precision of 95.7%. Moreover, our API responds under 700ms at 200 concurrent users. Finally, the evaluated System Usability Scale Score is 86.4, which indicates excellent usability.
DOI: http://doi.org/10.5281/zenodo.20230063
