Discovering Domain Vocabularies Based on Citation Co-word Network

被引：0

作者：

Cheng Q. ^{[1
]}

Wang J. ^{[1
]}

Lu W. ^{[1
]}

机构：

[1] (School of Information Management, Wuhan University, Wuhan 430072, China) (Information Retrieval and Knowledge Mining Laboratory, Wuhan University

来源：

Data Analysis and Knowledge Discovery | 2019年 / 3卷 / 06期

关键词：

Basic Vocabulary; Citation Co-word Network; Co-word Analysis; PageRank; Word Frequency;

D O I：

10.11925/infotech.2096-3467.2018.1159

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

[Objective] This paper identifies basic vocabularies of a specific domain from academic papers, aiming to grasp the knowledge structure and development context. [Methods] We combined the citation network and the co-word analysis to construct a citation co-word network. Then, we used the PageRank algorithm to evaluate the importance of the candidate words. We examined the proposed method with 110,360 articles in computer science. [Results] Our new method was compared with the word frequency method and co-word analysis qualitatively and quantitatively. We found that the proposed method performed well, and the average precision of a blind selection experiment reached 72.6%. [Limitations] The proposed method was only examined with computer science articles. [Conclusions] The new strategies could improve the performance of basic vocabulary discovery in one specific domain. © 2019 The authors.

引用

页码：57 / 65

页数：8

共 27 条

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