文献类型：期刊文献

中文题名：百度学术的数据整合——基于学术数据库覆盖率的案例研究

英文题名：Data Integration of Baidu Academic Search System——Case Study Based on Academic Database Coverage

作者：洪道广[1];缪灵敏[1]

机构：[1]华东理工大学图书馆,上海200237

年份：2018

卷号：38

期号：3

起止页码：133

中文期刊名：现代情报

外文期刊名：Journal of Modern Information

收录：CSTPCD;;国家哲学社会科学学术期刊数据库;CSSCI:【CSSCI2017_2018】；

语种：中文

中文关键词：百度学术;数据整合;文献检索;案例研究

外文关键词：Baidu academic system; data Integration; literature retrieval; case study

摘要：通过案例比较百度学术平台与来源数据库的检索结果,研究百度学术的数据整合,结果显示百度学术对中国知网、万方数据、维普期刊的2010-2016年中文期刊覆盖率大于96%,学位论文覆盖率大于90%;对比2000-2016的英文期刊数据百度学术对SCI&SSCI、EI数据库覆盖率大于94%,对Elsevier、Springer、Wiley、ACM、Emerald全文系统数据库覆盖率大于95%。但百度学术收集的专利、外文学位论文等数据不全面,对文献的分类准确性还需进一步提高。
By comparing the results of Baidu academic platform and source database with a retrieval case,this paper studied the data integration of Baidu academic System.Chinese journal papers coverage was greater than 96%,dissertations were greater than 90% to CNKI,Wanfang or VIP system from 2010 to 2016.The English journal papers coverage was greater than 94% to SCISSCI,EI system,more than 95% to Elsevier,Springer,Wiley,ACM,Emerald fulltext systems from 2000 to 2016.But collection of patents,foreign dissertations and other data was not comprehensive,the accuracy of the literature classification needed to be further improved in Baidu academic.