文献类型：期刊文献

中文题名：多源数据的文献计量功能发展及其比较研究

英文题名：Development and Comparative Study of Bibliometric Function of Multi-source Data

作者：朱雯[1];陈荣[1];孙济庆[1]

机构：[1]华东理工大学科技信息研究所

年份：2019

卷号：0

期号：10

起止页码：66

中文期刊名：图书馆理论与实践

外文期刊名：Library Theory and Practice

收录：国家哲学社会科学学术期刊数据库;CSSCI:【CSSCI_E2019_2020】；

语种：中文

中文关键词：多源数据;学术数据库;学术搜索引擎;文献计量功能

外文关键词：Multi-source Data;Academic Database;Academic Search Engine;Bibliometric Function

摘要：文章将文献计量功能的发展分为简单排序计量、指数化和模型化、可视化和智能化三个阶段,以多源数据——学术搜索引擎(谷歌学术、百度学术)和学术数据库(Web of Science、Scopus、中国知网和维普数据库)为研究对象,分析学术搜索引擎和学术数据库文献计量功能的发展特点及其差异,并从数据来源、计量内容、计算方法、结果呈现方式四个方面比较学术搜索引擎和学术数据库的文献计量功能.结果发现:学术搜索引擎和学术数据库的文献计量功能均发展到可视化和智能化阶段,学术数据库在计量种类以及计量结果呈现的可视化方面优于学术搜索引擎,学术搜索引擎的数据来源广于学术数据库,且二者均需加强知识语义和文献关系的计量.
The development of the bibliometric function is divided into stages of simple sorting, indexing and modeling, visualization and intelligence. Taking the multi-data source-the academic search engine(Google Scholar, Baidu Scholar) and the academic database(Web of Science, Scopus, CNKI and VIP Database) as research objects, the paper compares the bibliometric functions of academic search engine and academic database from aspects of data source, measurement content, calculation method and result presentation. It is found that the bibliometric functions of academic search engine and academic database have developed into a visual and intelligent stage. The academic database is superior to the academic search engine in the category of bibliometric and the visualization of the measurement results. While, the data sources of academic search engine are more extensive than academic database. And both of them need to strengthen the knowledge semantics and the measurement of the literature relationship.