Recommender System For Educational Analysis In Prediction of Appropriate Career & Domain Recommendations using Machine Learning Techniques

International Journal of Machine Learning and Networked Collaborative Engineering

View Publication Info
 
 
Field Value
 
Title Recommender System For Educational Analysis In Prediction of Appropriate Career & Domain Recommendations using Machine Learning Techniques
 
Creator Cherukuri, Praneet Amul Akash
 
Subject Machine Learning
Big Data
Recommender Systems
Bayesian Classifier
 
Description These days Career and Domain options have always been a very big ambiguous decision-making process for many prospective aspirants. Many aspirants make substantial domain changes very late in their career which may result in drastic effects on their career as well as their financial status. Many reports suggested that companies have suffered huge losses because of making wrong choices regarding the domain and employee interest. Hence providing a common platform early in the education sector for both the aspirants as well as companies that would provide appropriate domain suggestions for aspirants as well as right employee choices for companies would be highly beneficial that could help in generating better results when compared to the traditional ways of career choices employment. In this research, we are proposing a recommender system based model that would bridge the gap and help in formulating future needs
 
Publisher SR Informatics, New Delhi, India
 
Date 2019-11-10
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://www.mlnce.net/index.php/Home/article/view/100
 
Source International Journal of Machine Learning and Networked Collaborative Engineering; Vol. 3 No. 03 (2019): Volume No 03, Issue No 03; 135-142
2581-3242
 
Language eng
 
Relation http://www.mlnce.net/index.php/Home/article/view/100/62
 
Rights Copyright (c) 2020 International Journal of Machine Learning and Networked Collaborative Engineering
 

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