Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)

A Framework for Machine Learning Based Support System for Post-graduation Admission with the Case Study Conducted on D.K.M. College for Women, Vellore

Authors
M. Vasumathy1, *, R. Hamsaveni1, C. Jayashree1, S. Ellakiya Priya1
1Department of Computer Science and Application, D.K.M. College for Women, Vellore, India
*Corresponding author. Email: Vasudini2022@gmail.com
Corresponding Author
M. Vasumathy
Available Online 10 May 2023.
DOI
10.2991/978-94-6463-162-3_24How to use a DOI?
Keywords
Machine learning; Admission support system; knowledge based system; SVM; KNN algorithm
Abstract

India and other developing nations face difficulties building effective higher education systems, particularly when it comes to female students. Although the government made an effort, our nation did not benefit from its innovative and excellent educational policies. Indians still have a lot of issues with our educational system. The Indian government is aware that the current state of the world presents unique difficulties for the higher education sector. The UGC noted that a broad range of abilities will be expected of graduates in the humanities, social sciences, natural sciences, and business, as well as in a variety of professional fields like hospitality, tourism, agriculture, law, management, medical, and engineering. This knowledge cannot be adequately imparted during graduation, which ultimately leads to inadequate job. These include inadequate facilities and infrastructure, open seats in academic fields and poor faculty members thereof, low student enrollment rates, outdated and ineffective teaching strategies, falling standards for research, unmotivated students, crammed and cramped classrooms, and pervasive geographic, economic, gender, and racial imbalances. The post-graduation admission rate has significantly decreased in the past year at D.K.M. college for women in Vellore. A machine learning-based predictive analysis system is proposed to provide recommendations to improve PG admission. Taking into account the aforementioned scenario, the proposed work is primarily focused on the identification of issues, challenges, and decline factors of post-graduation admission from the perspectives of students, parents, teaching staffs, and management.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
10 May 2023
ISBN
978-94-6463-162-3
ISSN
2352-5428
DOI
10.2991/978-94-6463-162-3_24How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - M. Vasumathy
AU  - R. Hamsaveni
AU  - C. Jayashree
AU  - S. Ellakiya Priya
PY  - 2023
DA  - 2023/05/10
TI  - A Framework for Machine Learning Based Support System for Post-graduation Admission with the Case Study Conducted on D.K.M. College for Women, Vellore
BT  - Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
PB  - Atlantis Press
SP  - 265
EP  - 275
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-162-3_24
DO  - 10.2991/978-94-6463-162-3_24
ID  - Vasumathy2023
ER  -