Break Down Resumes into Sections to Extract Data and Perform Text Analysis using Python
Arvind Kumar Sinha, Md. Amir Khusru Akhtar, Mohit Kumar · International Journal on Recent and Innovation Trends in Computing and Communication · 2023
The objective of AI-based resume screening is to automate the screening process, and text, keyword, and named entity recognition extraction are critical. This paper discusses segmenting resumes in order to extract data and perform text analysis. The raw CV file has been imported, and the resume data cleaned to remove extra spaces, punctuation and stop words. To extract names from resumes, regular expressions are used. We have also used the spaCy library which is considered the most accurate natural language processing library. It includes already-trained models for entity recognition, parsing, and tagging. The experimental method is used with resume data sourced from Kaggle, and external Source (MTIS).