AUTOMATIC CV RANKING USING DOCUMENT VECTOR AND WORD EMBEDDING

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. 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 vectors with word embedding. Experiments show that word embedding method is more effective than the document vector.