Publication Date

Spring 2023

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

William Andreopoulos

Second Advisor

Nada Attar

Third Advisor

Navrati Saxena

Keywords

natural language generation

Abstract

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.

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