Resume Classification and Ranking using KNN and Cosine Similarity

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IJERTV10IS080057
Resume Classification and Ranking using KNN and Cosine Similarity

Rajath V , Riza Tanaz Fareed , Sharadadevi Kaganurmath

One of the most important and crucial task for any company is to hire an ideal candidate for their job role. Traditional hiring practises are becoming ineffective as online recruitment grows in popularity. The traditional methods normally entail a time-consuming process of manually looking through all of the individuals who have applied, examining their resumes, and then establishing a shortlist of prospects who should be interviewed. Job seeking has grown both wiser and more accessible in our technological age. Companies receive a large number of resumes/CVs, many of which are not well-structured. There has been a great deal of effort put into the job search. The process of picking a candidate based on their résumé, on the other hand, has not been completely automated. KNN Algorithm is used to classify the resumes according to their respective categories and Cosine Similarity is used to find out how close the candidate's resume is to the job description and they are ranked accordingly.