Evaluating a method to detect temporal trends of phrases in research documents

H. Abe, S. Tsumoto
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引用次数: 3

Abstract

In text mining processes, the importance indices of the technical terms play a key role in finding valuable patterns from various documents. Further, methods for finding emergent terms have attracted considerable attention as an important issue called temporal text mining. However, many conventional methods are not robust against changes in technical terms. In order to detect remarkable temporal trends of technical terms in given textual datasets robustly, we propose a method based on temporal changes in several importance indices by assuming the importance indices of the terms to be a dataset. Empirical studies show that two representative importance indices are applied to the documents from two research areas. After detecting the temporal trends, we compared the emergent trend of the technical phrases to some emergent phrases given by a domain expert.
评价一种检测研究文献中短语时态趋势的方法
在文本挖掘过程中,专业术语的重要度指标对从各种文档中发现有价值的模式起着关键作用。此外,发现紧急术语的方法作为一个重要的问题被称为时态文本挖掘,已经引起了相当大的关注。然而,许多传统方法对于技术术语的变化并不健壮。为了稳健地检测给定文本数据集中技术术语的显著时间趋势,我们提出了一种基于多个重要指标的时间变化的方法,该方法将术语的重要指标假设为一个数据集。实证研究表明,两个具有代表性的重要指数适用于两个研究领域的文献。在发现时态趋势后,我们将技术短语的出现趋势与领域专家给出的一些出现趋势进行比较。
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