Automatic CV Ranking Using Document Vector and Word Embedding
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Abstract
This research is based on the practical facts related to the human resource department of any organization for the recruitment of personnel. As it is a challenging and crucial aspect for any organization to select the right talent for the right place. This paper helps in expertise finding in the different fields of Computer Science. Employers receive a bunch of resumes upon job openings. And the candidates are also interested are in sifting the best among the applicants. Screening the best candidate among the pool of resumes is a laborious task. This paper proposes an informational retrieval-based resume ranking scheme for screening and ranking the candidate's resumes. The primary purpose of this research study is to exploit the class NLP techniques to perform the information retrieval task for resume ranking based on job description similarity. In this proposed methodology, we compared document vectorswith word embedding. Experiments show that word embedding method is more effective than the document vector.
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Pakistan Journal Emerging Science and Technologies (PJEST) in collaboration with Govt. Islamia Graduate College Civil Lines Lahore, Pakistan is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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