Investigating Social Network Analysis (SNA) for recommendation systems in science research discovery

科学研究人员和学者经常面临的挑战是跟上相关新研究的步伐。由于文献来源不同，并且相对缺乏强大的工具来支持特定于上下文的相关方法来探索学术文献，因此这项任务可能具有挑战性。随着时间的推移，数字图书馆的规模也在不断扩大，新文学的不断涌现，可供探索的文学资源也在不断扩大。虽然提高文献的可访问性对研究人员有利，但它给文献探索系统带来了压力，使其无法支持更大的数据集，从而使数字图书馆的探索成为一个更具挑战性的过程，需要新的工具、技术和基础设施。

A frequent challenge for science researchers and scholars is to keep up to date with relevant new research. This task can be challenging due to the disparate sources of literature and the relative lack of powerful tools to support context-specific and relevant methods for exploring academic literature. As time goes by, digital libraries continue to expand due to new literature being written, thus continually enlarging the pool of literature to explore. Although improving the accessibility of literature should benefit researchers, it puts pressure on literature exploration systems to support larger data sets, thus making exploration of digital libraries a more challenging process in need of novel tools, techniques and infrastructure.