Resume Parser and Job Recommendation System using Machine Learning

Abstract

In the today’s job market, both job seeker and employers face challenge for finding skills and qualification with job opening. To streamline this process, the development of innovative tools and technologies is essential. To overcome this challenge, in this paper we proposed machine learning and natural language processing based technique for the extraction of skills from the resumes for job openings. The proposed technique consists of two pivotal components: a Resume Parser and a Job Recommender. The Resume Parser is implemented in Python which consist of libraries such as spaCy and PDFMiner to extract vital resume details. The extracted skills form the foundation for generating job recommendations. The Job recommender works on a comprehensive job dataset. To provide job recommendations, the proposed system uses Tf-Idf vector to analyse job titles and cosine similarity for job recommendation recommend.

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