A calculation method for the development trend of subject keywords

Article type: Research Article

Authors: Li, Yuyao^{a; b}

Affiliations: [a] School of Computer Science, South China Normal University, Guangzhou 510631, Guangdong, China | [b] School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou 510006, Guangdong, China

Correspondence: [*] Corresponding author: Yuyao Li, School of Computer Science, South China Normal University, Guangzhou 510631, Guangdong, China. E-mail: everybit@163.com.

Abstract: 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.

Keywords: Domain-specific common word sets, dynamic characters of keywords, subject trend, TF-IDF

DOI: 10.3233/JCM-193789

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 20, no. 1, pp. 301-312, 2020