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A social recommendation system for academic collaboration in undergraduate research
Authors:Yang Liu  Chen Yang  Jian Ma  Wei Xu  Zhongsheng Hua
Abstract:Academic collaboration plays an important role in undergraduate research. Current methods rely on offline social contacts for undergraduate students to collaborate with academic staff members in universities and research institutions. In big data era, it is difficult for undergraduate students to find suitable research project opportunities and supervisors to work with. This paper proposes a social recommendation system for undergraduate students to find research project opportunities and work with research project teams on an academic collaboration network. The proposed recommendation method integrates relevance, connectivity, and quality modules, where profiles of undergraduates are constructed with their self‐claimed information, research activities (e.g., studying and reading research publications and reading research projects), and social connections in the academic collaboration network. Suitable research projects are recommended based on the undergraduates' profiles. Experiments are conducted, and the results have shown that the proposed social recommendation system can facilitate undergraduates' selection of research projects.
Keywords:academic collaboration network  data mining  social recommendation systems  undergraduate research
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