Qianyi Hou1, Shuyuan Bao2, Longxi Wang3, Zhengxi Hou4, Tianyuan Zhang5
1Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China
2Beijing No. 55 High School, Beijing, China
3Beijing Huijia Private School, Beijing, China
4Tianjin WeiMing School, Xiqing, Tianjin, China
5Beijing New Essence, Beijing, China
In recent years, studying abroad has become an important way for more and more people to achieve their personal development goals. However, with a wide range of study abroad programs and varying standards, choosing a suitable study abroad program has become a challenge. This website proposes a recommendation system for studying abroad projects based on causal reasoning. This website conducts causal analysis and inference of user basic information to generate appropriate decisions. Predicting and inferring conclusions based on causal reasoning will lead to more precise planning actions, enabling international students to choose their study abroad projects more accurately, thereby improving the effectiveness of studying abroad. This website is based on a causal reasoning algorithm for career/future planning goals and has designed a corresponding recommendation system for study abroad projects, providing a scientific and reliable way for study abroad planners to choose their study abroad projects.
causal inference, recommendation algorithm, SCM
Qianyi Hou, Shuyuan Bao, Longxi Wang, Zhengxi Hou, Tianyuan Zhang. Causal Inference-based Study Abroad Program Recommendation System. The Frontiers of Society, Science and Technology (2023) Vol. 5, Issue 16: 40-45. https://doi.org/10.25236/FSST.2023.051608.
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