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

机译:评估一种检测研究文件中短语的时间趋势的方法

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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.
机译:在文本挖掘过程中,技术术语的重要性指标在寻找来自各种文件的宝贵模式方面发挥着关键作用。此外,寻找紧急术语的方法引起了相当大的关注,作为一个称为时间文本挖掘的重要问题。然而,许多传统方法对技术术语的变化并不稳健。为了稳健地检测给定文本数据集中的技术术语的显着时间趋势,我们提出了一种基于几个重要指标的时间变化的方法,假设术语的重要性指数是数据集。实证研究表明,两个代表性重要指标适用于两项研究领域的文件。在检测到时间趋势之后,将技术短语的紧急趋势与域专家给出的一些紧急短语进行了比较。

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