Application Tracking System Using Natural Language Processing

Abstract— Screening resumes from a large pool is a difficult task, and recruiters waste a lot of time reading through each resume. We can optimize this labor-intensive process of screening countless resumes and make our search process much easier. Using Named Entity Recognition (NER), the task of screening resumes is automated with all the extraneous information discarded, making it simpler for recruiters to examine each resume more thoroughly in less time. The proposed method uses phrase-matching similarity to compare the resume to the job description after the text mining process has been completed. The best candidates for a particular job opening can then be determined using the computed ranking scores. The visual representation of the ranking data is aided by data visualization