TY - GEN
T1 - Artificial Intelligence in Study-Abroad Program Recommendations
AU - Gao, Yang
AU - Wang, Xiaocheng
AU - Shi, Jintao
AU - Liu, Zhongyan
AU - Wei, Zejin
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Students willing to study abroad may find it challenging to go through tons of website pages on the application process. The complication of the studying-abroad application process makes it even harder for many students to figure out their dream and fit schools. With artificial intelligence being widely promoted across different subjects and disciplines, we made attempts to incorporate artificial intelligence into education program recommendations. We thus designed a recommendation system for studying-abroad programs through the K-nearest neighbor algorithm. The designed system may recommend up to six colleges and universities to students according to their input of grade average points, language testing scores, acceptable fees, target majors, and location preference. In addition, the analysis of the application plan and the report on the academic entrance requirements are also offered through the system. The project simplifies the application process and thus saves the time and energy of the applicants.
AB - Students willing to study abroad may find it challenging to go through tons of website pages on the application process. The complication of the studying-abroad application process makes it even harder for many students to figure out their dream and fit schools. With artificial intelligence being widely promoted across different subjects and disciplines, we made attempts to incorporate artificial intelligence into education program recommendations. We thus designed a recommendation system for studying-abroad programs through the K-nearest neighbor algorithm. The designed system may recommend up to six colleges and universities to students according to their input of grade average points, language testing scores, acceptable fees, target majors, and location preference. In addition, the analysis of the application plan and the report on the academic entrance requirements are also offered through the system. The project simplifies the application process and thus saves the time and energy of the applicants.
KW - KNN
KW - Recommendation system
KW - Study-abroad programs
UR - https://www.scopus.com/pages/publications/85128775842
U2 - 10.1007/978-3-030-96296-8_92
DO - 10.1007/978-3-030-96296-8_92
M3 - 会议稿件
AN - SCOPUS:85128775842
SN - 9783030962951
T3 - Lecture Notes in Networks and Systems
SP - 1014
EP - 1021
BT - New Realities, Mobile Systems and Applications - Proceedings of the 14th IMCL Conference
A2 - Auer, Michael E.
A2 - Tsiatsos, Thrasyvoulos
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th International Conference on Interactive Mobile Communication, Technologies and Learning, IMCL 2021
Y2 - 4 November 2021 through 5 November 2021
ER -