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
M. Vasumathy (),
R. Hamsaveni,
C. Jayashree and
S. Ellakiya Priya
Additional contact information
M. Vasumathy: D.K.M. College for Women, Department of Computer Science and Application
R. Hamsaveni: D.K.M. College for Women, Department of Computer Science and Application
C. Jayashree: D.K.M. College for Women, Department of Computer Science and Application
S. Ellakiya Priya: D.K.M. College for Women, Department of Computer Science and Application
A chapter in Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023), 2023, pp 265-275 from Springer
Abstract:
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and infrastructure, open seats in academic fields and poor faculty members thereof, low student enrollment rates, outdated and ineffective teaching strategies, falling standards for research, unmotivated students, crammed and cramped classrooms, and pervasive geographic, economic,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.
Keywords: Machine learning; Admission support system; knowledge based system; SVM; KNN algorithm (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-162-3_24
Ordering information: This item can be ordered from
http://www.springer.com/9789464631623
DOI: 10.2991/978-94-6463-162-3_24
Access Statistics for this chapter
More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().