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.
