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Topic Summary Views for Exploration of Large Scholarly Datasets

机译:探索大型学术数据集的主题摘要视图

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摘要

In this article, we present the E-sch approach for exploration of large scholarly datasets based on topic summary views . The goal of E-sch is to semantically summarize the dataset related to a potentially very large number of scholar publications (e.g., millions) by a list of few thousands topics, up to an ultimate list of hundreds of topic summaries to use for analyzing research dynamics and evolution at a more semantic, high-level of inquiry. Filter and Slice operators are defined in E-sch to enforce interactive scholarly data exploration along thematic and temporal perspectives.
机译:在本文中,我们介绍了基于主题摘要视图的E-sch方法,用于探索大型学术数据集。 E-sch的目标是通过几千个主题的列表,从语义上总结与可能非常大量的学者出版物(例如,数百万个)相关的数据集,直至最终用于分析研究的数百个主题摘要的最终列表。动态和进化,从语义上,更高层次上进行询问。在E-sch中定义了Filter和Slice运算符,以沿主题和时间角度实施交互式学术数据探索。

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