An intelligent recommendation system framework for student relationship management

In order to enhance student satisfaction, many services have been provided in order to meet student needs. A recommendation system is a significant service which can be used to assist students in several ways. This paper proposes a conceptual framework of an Intelligent Recommendation System in order to support Student Relationship Management (SRM) for a Thai private university. This article proposed the system architecture of an Intelligent Recommendation System (IRS) which aims to assist students to choose an appropriate course for their studies. Moreover, this study intends to compare different data mining techniques in various recommendation systems and to determine appropriate algorithms for the proposed electronic Intelligent Recommendation System (IRS). The IRS also aims to support Student Relationship Management (SRM) in the university. The IRS has been designed using data mining and artificial intelligent techniques such as clustering, association rule and classification

An intelligent recommendation system framework for student relationship management

Many universities have implemented innovative information systems and services to help their students and to support academic management processes. This paper proposes a conceptual framework to support Student Relationship Management (SRM) for Thai universities in the new electronic era. This conceptual framework assists students to choose appropriate course and subjects for their studies. The objectives of this article aim to broaden an understanding of SRM and related issues focus on recruitment, enrolment and course counseling. An Intelligent Recommendation System framework (IRS) has been designed using data mining and artificial intelligent techniques such as clustering, association rule and fuzzy logic. These techniques will be used to assess the performance of the students and to provide appropriate recommendations for their choice of courses and subjects