A novel firefly driven scheme for resume parsing and matching based on entity linking paradigm

Abstract

In this paper, contemporary Natural Language Processing techniques have been leveraged to demonstrate the capability of data-driven HR towards significant improvement in the quality and speed of the whole recruiting process. Firstly, by using NLP, a resume parser has been implemented to analyze the most crucial recruitment parameters. Thereafter, ability to display a pie chart for a candidate has been employed in the algorithmic structure of the parser to prepare a powerful tool for the resume matching based on job criteria. To determine the efficacy and accuracy of the proposed resume ranker, an enhanced rival modern optimizer, i.e., firefly ranking algorithm is applied to accelerate the speed of ranking algorithm. An overall accuracy of 94.19% has been achieved by the proposed approach. The results indicate that the resume parser has been incorporated with robust techniques and hence concedes to the accuracy of the results.

Subject Classification:

• 03B52
• 68T20
• 68T50

Keywords:

• Data-driven HR
• Firefly algorithm
• NLP
• Resume parser
• Resume matching