Requires intelligent analysis of semi-structured resumes to find the best fit for an open position. Standard search techniques still require significant curation.
- 1.Automated the process of analyzing the resume, identifying significant facts and filtering resumes.
- 2.Generating a knowledge graph.
- 1.Designed a multilayered deep learning network to analyze the resumes and extract significant facts from the resume.
- 2.The facts were then used to construct a knowledge graph about the person.
- 3.A deep learning model was designed to use the data present within the knowledge graph to predict the propensity of the person getting shortlisted for a job.
Turn around time for finding relevant resumes reduced by 50%