Open AccessMajor Courses Selection using Three Layer Factors: A Recommender System
Author(s) -
G. Mounika,
B. S. Chaitanya,
Chandan K. Reddy,
Jonnalagadda. Surya Kiran
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d9100.118419
Subject(s) - graduation (instrument) , computer science , selection (genetic algorithm) , representation (politics) , face (sociological concept) , layer (electronics) , machine learning , artificial intelligence , data science , mathematics education , psychology , engineering , political science , sociology , mechanical engineering , social science , chemistry , organic chemistry , politics , law
Data mining is one of the significant territories. Since numerous understudies will face difficulties and disarray while picking their significant courses in their graduation and even in the wake of picking their real few are in danger of bombing in it because of less intrigue and endeavors, so we should have a model to discover their interests and help them to pick their real seminars all alone. This methodology proposes three-layered representation which could be adjusted consecutively for the profound established arrangement. The recommended model would be utilized to early identify students who may be in danger because of miss coordinate determinations of the major course’s groupings. The essential target incorporates the disclosure of examples, wherein the students can choose or lessen danger of failure of their major courses