Student Admission Recommender - Web interface and AI Algorithm.
Documentation: https://www.stuvia.com/en-nl
https://www.studypool.com/
Source code : https://www.piecex.com/
then search by application name.
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Introducing the Student Admission Recommender System (SARS), an intelligent recommendation engine designed to help students select the best universities for their graduate courses in KSA. SARS is a specialized recommender system that analyzes various datasets/corpora of previous high school students, their voting on multiple universities, and their colleges' characteristics to predict a list of best colleges for admissions of new students.
SARS uses a unique approach that differentiates between the preference/voting of the college and a student profile. The preference/voting of each college is represented as a corpus (dataset) of features, while the student profile is represented with the same terms and constructed by analyzing the content done by the user. The architecture of SARS has three main components: Data Analyzer, Classifier, and Visualization, which provide an easy-to-use interface for non-technical users.
SARS uses advanced algorithms such as datamining cosine similarity algorithm, which has proven to be the best in classifying universities according to students' preferences and voting. Other algorithms like random forest and nearest neighbors failed to achieve high precision in classifying and recommending colleges.
The system's user-friendly interface allows users to input their information and ambitious requirements for education specialties, and the system will recommend colleges based on various profiles/ratings and data entered by the user. The application will list out the number of colleges suitable for the user, along with information such as education roles, prices, location, etc.
SARS is a powerful tool that is consistent with the country's government 2030 vision. Its data preprocessing is an essential part, where the corpus/dataset is merged, cleaned, transformed, resampled, and reformatted to CSV, then transformed into SQL format to be in the form suitable for the classifier in the server. OLAP analysis may be used for the graphical representation part after classification and analysis using LARAVEL environment for a responsive and attractive user interface.
With SARS, students can make informed decisions about their graduate courses and select the best universities that align with their preferences and ambitions. Try SARS today and take the first step towards your successful career path!