Key points are not available for this paper at this time.
In the today's era of endless career options, the challenge to get that one ideal job that aligns best with individual's skills and interests is absent due to lack of personalized recommendations and lack of guidance about resume making it becomes challenging to find best jobs and get shortlisted for the hiring process of a company. This paper introduces a novel approach to address these challenges by the development of a Career Crafter AI - A Resume analysis and Job Recommendation System. Knowing the limitations of existing recommendations systems that primarily rely on individuals provided interests, our system, implemented on the e-learning platform for skill building, Level Up, goes beyond the traditional approach of recommendation system. Using Vector Machine algorithm and the cosine similarity our system classifies the users based on their skills and profile mentioned on the platform and Natural Language Processing enables to provide the tips and recommendation to improve our resume and get the insights about the user for better recommendation. The recommendation engine utilizes these insights to provide accurate and best fit jobs to the users and as well as provide potential candidate for job roles to the recruiters This research paper aims to provide a one stop destination for learners to improve their resume for getting an edge during shortlisting and interviews and to transform and optimize the job recommendation systems by offering a more personalized and effective approach, empowering individuals to navigate their career paths with confidence and precision.
Building similarity graph...
Analyzing shared references across papers
Loading...
Akshay Rajput
Akanksha Dubey
Rishabh Thakur
Graphic Era University
Building similarity graph...
Analyzing shared references across papers
Loading...
Rajput et al. (Fri,) studied this question.
www.synapsesocial.com/papers/68e6d7efb6db643587655087 — DOI: https://doi.org/10.1109/istems60181.2024.10560126