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arXiv · 2103.14934

Community-based Cyberreading for Information Understanding

Zhuoren Jiang·Xiaozhong Liu·Liangcai Gao·Zhi Tang
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Abstract

Although the content in scientific publications is increasingly challenging, it is necessary to investigate another important problem, that of scientific information understanding. For this proposed problem, we investigate novel methods to assist scholars (readers) to better understand scientific publications by enabling physical and virtual collaboration. For physical collaboration, an algorithm will group readers together based on their profiles and reading behavior, and will enable the cyberreading collaboration within a online reading group. For virtual collaboration, instead of pushing readers to communicate with others, we cluster readers based on their estimated information needs. For each cluster, a learning to rank model will be generated to recommend readers' communitized resources (i.e., videos, slides, and wikis) to help them understand the target publication.

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Zhuoren Jiang, Xiaozhong Liu, Liangcai Gao, Zhi Tang. 2021-03-27. Community-based Cyberreading for Information Understanding. https://arxiv.org/abs/2103.14934

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