Layout aware resume parsing using nlp and rule-based techniques

Abstract

As a result of the rapid development seen in the field of IT, there has been a surge in the number of students choosing IT field related degrees in recent years When those students try to secure job a better fob position in the field of IT, resume plays a vital role as it is often the first document a recruiter will see in the recruitment process. Therefore, this paper introduces a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume. This output can be used as the input for the resume content scoring model as a resume content review system to get feedback for the resume. When comparing existing methods with the proposed system, the layout of the resume would be considered in the proposed system, and it would extract content for each section. In addition to that, the proposed system would extract all the text content, but existing systems only extract the entities. In summary, this study is focused on developing a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume for an accurate resume review.