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A calculation method for the development trend of subject keywords

机译:主题关键字发展趋势的计算方法

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SIGNIFICANCE: The complex network structure information such as citation network and co-authored network provides rich structural information for subject trend research, thus research on deep mining of existing static structure information to obtain keyword trend receives less attention. Both dynamic method for the extraction of domain-specific common word set and the method for calculating keywords dynamic characteristic (DC value) proposed in this paper can be used as basic methods and parameters for subject trend research.METHOD: Employed mature and widely used TF-IDF algorithm as the word frequency calculation tool, this paper use stable static structural information such as publishing date and journal name to propose a method of calculating the dynamic characteristic of subject keywords based on stable structure such as time, journal name and domain-specific common word set.RESULT: The experimental results show that the keywords' DC value is positively correlated to the change trend of keywords based on time.
机译:意义:传统网络结构信息如引文网络和共同撰写的网络,为主题趋势研究提供了丰富的结构信息,从而研究了现有静态结构信息的深度挖掘,以获得关键字趋势的影响较少。用于提取域特定的公共词组的动态方法和计算本文提出的关键字动态特性(DC值)的方法可用作主题趋势研究的基本方法和参数。方法:采用成熟和广泛使用的TF -IDF算法作为Word频率计算工具,本文使用稳定的静态结构信息,例如发布日期和日志名称,提出一种基于稳定结构计算主题关键字的动态特性的方法,例如时间,日记名和特定于域公共词Set.Result:实验结果表明,关键字'DC值与基于时间的关键字的变化趋势正相关。

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