A social recommendation system for academic collaboration in undergraduate research

• Published in: Expert systems 2019-04, Vol.36 (2), p.n/a
• Main Authors: Liu, Yang, Yang, Chen, Ma, Jian, Xu, Wei, Hua, Zhongsheng
• Format: Article
• Language: English
• Subjects: academic collaboration network; Collaboration; College students; Colleges & universities; Data management; data mining; R&D; Recommender systems; Research & development; Research projects; Scientific papers; social recommendation systems; Students; Supervisors; undergraduate research
• ISSN: 0266-4720; 1468-0394
• DOI: 10.1111/exsy.12365

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.