Open AccessRecommendation System for Human Resource Department
Author(s) -
Ulka Khobragade
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.39886
Subject(s) - schedule , similarity (geometry) , quality (philosophy) , computer science , cosine similarity , human resources , knowledge management , operations research , operations management , artificial intelligence , management , engineering , pattern recognition (psychology) , economics , philosophy , epistemology , image (mathematics) , operating system
The objective is to find suitable skilled employees for the job among different departments within the organization. For finding the quality of an applicant or even the already employed employee, the HRs of companies goes through a lot of hectic schedule, time consuming processes, decision making, etc. In this case, Recommendation System, which is a part of Machine Learning, proves to be effective in making decisions on behalf of the HRs if an employee or an applicant is suitable enough for the job. The aim of the project is to predict whether the already employed employees, who belong to different department within the organization can perform well or not if assigned to a different department. Keywords: Recommendation system, Collaborative Learning, K-NN, Similarity, Similarity Correlation, Cosine etc.