Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Jobseekers often face difficulties in tailoring their resumes to specific job descriptions
and manually applying for multiple roles, which is time-consuming and inefficient. To
address this, we propose a system that automates the job-seeking process with an easy-
to-use approach. Users can upload their resumes, and the system analyzes them to extract
key details. It recommends top job positions that match the user’s skills and experience
and identifies relevant job listings using Naive Bayes Classifier. The system rewrites and
optimizes resumes to align with industry standards and specific job requirements with
the help of T5(text to text transfer transformer). It automates the process of applying
to jobs, saving significant time and effort. By combining resume optimization, job
recommendations, and automated applications, our system simplifies and streamlines the
job search process for users.
"JOBSNAP : AN AUTOMATED RESUME REWRITE AND APPLYING SYSTEM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b850-b853, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506197.pdf
Downloads:
000402
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator