Abstract
There are more than 2800 higher education institutions in China, all of which have a wealth of basic attributes and introductory information. However, by investigating common university and college information service platforms, we find a problem that users cannot quickly access key information. Inspired by user profile and corporate portraits, we propose a university portrait system incorporating academic social networks. We first collect two types of data, then utilize text mining techniques integrated with statistics-based methods and topic-based methods to extract features and generate tags of universities. Additionally, we incorporate data related to the universities on the academic social network SCHOLAT.COM including scholars, academic news, courses and academic organizations to enrich our university portraits.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China under Grant U1811263, Grant 61772211 (Y. Tang), NSFC under Grant 11901210 and China Postdoctoral Science Foundation under Grant 2019M652924 (L. Lan).
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Lai, Y., Lan, L., Liang, R., Huang, L., Qiu, Z., Tang, Y. (2022). A University Portrait System Incorporating Academic Social Network. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2021. Communications in Computer and Information Science, vol 1492. Springer, Singapore. https://doi.org/10.1007/978-981-19-4549-6_3
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DOI: https://doi.org/10.1007/978-981-19-4549-6_3
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