期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2019
卷号：2241
页码：233-237
出版社：Newswood and International Association of Engineers
摘要：In a university system, the final year project is a
synthesis of all the knowledge the students have acquired
throughout the different years of their stay in the university.
This knowledge must be used to solve a specific problem.
Finding and selecting the appropriate project topic and
supervisor to supervise the students, presently is in most cases
very subjective. This paper presents a web based decision
support system that automates efficiently the management of
final year projects. The main contribution of the research is to
recommend project supervisors and project topic based Naïve
Bayes prediction.
The decision support framework is web based, developed
using JSP (Java-Server Pages), which integrates machinelearning
algorithms to allocate final year projects and
supervisor.
The developed system has been able to provide a platform
that maximizes the potentials of students and faculties
particularly to solve industry and community related
problems. This research has provided a platform to improve
the quality of final year research project in the higher
institutions of learning. It has also provided a rich platform for
available project prototypes and help to eliminate the problems
peculiar to lack of automation in final year project
management and decision making.
关键词：Data Mining; Classification algorithm;
Naïve;Bayes algorithm; final year project management
