Resume Parser Analysis Using Machine Learning and Natural Language Processing

Abstract

Abstract: With the rise of online job application processes, submitting a resume has become easier than ever before. As a result, a larger number of individuals are impacted by this change. Many organizations still accept resumes by mail, which can cause challenges for their human resources departments. Sorting through a large number of applications to find the most suitable candidates can be a time-consuming process for these agencies. Job applicants submit resumes in a wide range of formats, including various fonts, font sizes, colors, and other design elements. Human resources departments are responsible for reviewing each application and selecting the most qualified candidate for the job. My suggestion is to incorporate natural language processing techniques into the project's parser to assist the human resources department or recruiting manager in analyzing the information provided in resumes. This approach can involve using keyword matching and other natural language processing methods to identify the most suitable candidates and obtain the most effective resumes. By doing so, the organization can improve its recruitment process and identify the best candidates for the job.