Master of Science (MS)
natural language generation
Generally candidates apply to multiple jobs with a single resume and do not tend to customize their resume to match the job description. This hampers their chances of getting a resume shortlisted for the job. The project aims to help such candidates build job tailored resumes that help them create a customized and targeted resume for a specific job or industry. The tool specifically targets candidates’ employment history, for resume content generation. We then use natural language processing
(NLP) techniques to extract and organize this data into a structured format for the dataset. We experiment with multiple variations of the dataset and cite ways to effectively build the dataset for the proposed task. After dataset creation, we use natural language generation by fine tuning GPT-2 to generate the resume content. Finally we report our findings with scope for improvements and future work.
Kale, Sumedh, "Job Tailored Resume Content Generation" (2023). Master's Projects. 1216.
Available for download on Tuesday, May 21, 2024