Bibliometric Analysis of the Semantic Mining Research Status with the Data from Web of Science

EasyChair Preprint 493

Abstract

By using the 2460 papers obtained from the Web of Science database from 1991 to 2018 as the research sample, this paper demonstrates a comprehensive bibliometric analysis of the research status, trends and hotspots in the domain of Semantic Mining. The results indicate that the current global semantic mining research is of great value; Knowledge is mainly distributed in computer science, engineering and linguistics; the international academic communications in semantic mining field are pretty prosperous, which are concentrated on three major region: East Asia, North America and West Europe. In addition, the research hotspots be shown in keywords co-occurring mapping is the research of technology which is represented by text mining, the research of theory which is represented by ontology and semantic network, and the research of application which is represented by knowledge discovery and information extraction. And the current research fronts can be categorized into two layers: the model research by using deep learning technology for semantic mining, the application research such as applying semantic mining to social media. Finally, we discussed to use the mathematical models of logistic curve to predict the number of papers in the future which told us the study is still in the growth stage at present and we need to grasp the golden age of the next five years.

Keyphrases: CiteSpace, Mapping of Knowledge Domain, Semantic Mining

@booklet{EasyChair:493,
  author    = {Mao Meixin and Zili Li and Zeng Li and Zhao Zhao and Yang Zhao},
  title     = {Bibliometric Analysis of the Semantic Mining Research Status with the Data from Web of Science},
  doi       = {10.29007/89vp},
  howpublished = {EasyChair Preprint 493},
  year      = {EasyChair, 2018}}