ABSTRACT: In this paper, we provide a sophisticated recommendation system for students considering enrolling in an undergraduate programme at an Indian university. The recommended system contains a predictive model that predicts students' academic achievement in addition to the functional elements of the collaborative filtering approach. The recommendation system may provide better suggesting techniques in accordance with the model's output values, and a sentiment analysis of the pupils is conducted. Based on the concept of a knowledge-based recommender system, this essay explored a high-level framework for an intelligent recommender system. Knowledge is applied, new information is discovered, and preferences and criticisms are inferred by the intelligent recommender system. An intelligent recommender system is built on a foundation of knowledge representation paradigms, learning processes, and reasoning mechanisms. It also includes five knowledge models for the many factors we might consider while making recommendations: users, things, domain, context, and critiques. The combination of the elements, among other things, uses the information, refreshes it, and makes inferences.
KEYWORDS:Recommendation system, predictive model, academic performance prediction, student relationship management (SRM)
AN INTELLIGENT RECOMMENDATION SYSTEM REGARDING THE UNDERGRADUATE PROGRAM IN THE INDIAN UNIVERSITIES BEFORE JOINING ANY EDUCATIONAL INSTITUTION USING COLLABORATIVE FILTERING APPROACH
T V SATHYANARAYANA
RESEARCH SCHOLAR
DR. ARCHANA TUKARAM BHISE
RESEARCH GUIDE
SHRI JAGADISHPRASAD JHABARMAL TIBREWALA UNIVERSITY