Smart Resume Analyser: A Case Study using RNN-based Keyword Extraction

Abstract

The pursuit of a reputable position in a company is a common goal shared by many people. For making this desire into reality their resume is the key to it. Making these resumes is a challenging task for many and modifying it is another time-consuming and burdensome task. Taking these problems into consideration and to make eye-catching resumes we have developed a smart resume analyser that can analyse the user’s resume, it intelligently identifies their skills and qualifications, enabling us to suggest the best-suited job titles for their profile. Furthermore, based on this analysis, our system generates recommendations for optimizing and enhancing the user’s resume, making it more appealing to potential employers. Through the utilization of NLP and ML technologies, our resume analyser provides personalised and effective solutions to job seekers, helping them stand out in today’s competitive job market. The information on the resume can be analysed and understood easily as NLP has the capability to understand and parse the information on the resume and extract the desired information efficiently. With the additional help from Python and its packages like streamlit, pymysql, etc. we can store the extracted data and give a rating based on the analysis of the stored data. After the rating is generated, we recommend some modifications like: adding sentences like my hobbies are, my goal is, add objectives, and add declaration and more. We also suggest a few sources through which the user can enhance their skills.