An Automated System for Transferring and Equivalence between Saudi Universities

Text-Mining is one of the most important areas of machine learning and data science. It has gained great momentum recently, where it is being employed in many different majors of university degrees to create a new level of services and applications. The education field has a significant effect on many parts of society, especially within universities. One of the critical issues that can face any student during their academic life is transferring to another university. This research depends on the techniques of Text-Mining and proposes a new algorithm for calculating the similarity rate between two subjects' descriptions. The rate will be used for an electronic equivalent system between subjects of two universities. Moreover, the system will manage the whole process and functions of transferring starting from the request until the final decision. The proposed system will address the problems of the current system which relate to cost, time, effort, and equity. The integration between the proposed web application and the proposed algorithm will create comprehensive processing for this issue. Finally, the testing and comparison shows the viability of the proposed method to applying it in the real environments. According to specialists, the equivalent manual process takes between 2 to 4 months, from the moment of receiving the papers from students until publishing the end results. Briefly, we propose a web-based system for online applications, which would include an auto similarity calculating function to enable the students make request by themselves, which will enable them to check the approximate end result which will be very accurate because we avoid the bias and difference among persons from this process. That is the primary goal of this research.