Visualising Scientific Topic Evolution

P. Deligiannis, Thanasis Vergoulis, Serafeim Chatzopoulos, Christos Tryfonopoulos
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引用次数: 1

Abstract

The automatic extraction of topics is a standard technique for summarizing text corpora from various domains (e.g., news articles, transport or logistic reports, scientific publications) that has several applications. Since, in many cases, topics are subject to continuous change there is the need to monitor the evolution of a set of topics of interest, as the corresponding corpora are updated. The evolution of scientific topics, in particular, is of great interest for researchers, policy makers, fund managers, and other professionals/engineers in the research and academic community. In this work, we demonstrate a prototype that provides intuitive visualisations for the evolution of scientific topics providing insights about topic transformation, merging, and splitting during the recent years. Although the prototype works on top of a scientific text corpus, its implementation is generic and can be easily applied on texts from other domains, as well.
可视化科学主题演变
主题的自动提取是一种标准技术,用于总结来自不同领域的文本语料库(例如,新闻文章、运输或物流报告、科学出版物),具有多种应用。由于在许多情况下,主题受到持续变化的影响,因此需要在相应的语料库更新时监视一组感兴趣的主题的演变。科学主题的演变尤其引起了研究人员、政策制定者、基金经理以及研究和学术界的其他专业人员/工程师的极大兴趣。在这项工作中,我们展示了一个原型,它为科学主题的演变提供了直观的可视化,提供了近年来主题转换、合并和分裂的见解。虽然原型工作在科学文本语料库之上,但它的实现是通用的,也可以很容易地应用于其他领域的文本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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