共查询到18条相似文献，搜索用时 265 毫秒
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Google Scholar在科技论文学术查新中的作用 总被引：4，自引：0，他引：4
Google Scholar是建立在Google搜索引擎上直接面向科研需要的学术资源的网络搜索工具,为广大学术查新工作者提供了极其方便的条件.阐述Google Scholar在科技论文学术查新中的作用,并分析其不足之处,提出了弥补方法. 相似文献
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为了探讨同行评议、影响计量学以及传统文献计量指标在科学评价中的有效性,本文选取F1000、Mendeley以及Web of Science、Google Scholar数据库,采用SPSS 19.0软件,将心理学与生态学的1,3篇论文的同行评议结果即F1000因子、Mendeley阅读统计、期刊影响因子,以及Web of Science、Google Scholar数据库中被引频次进行相关分析。结果表明:同行评议结果、传统引文分析指标以及以Mendeley为代表的影响计量指标具有低度正相关性,这意味着上述指标在科学评价中审视视角的不同以及数字时代科学评价的多维构成;心理学筛选数据中F1000因子与期刊影响因子相关度几近为0,这一结论进一步证实了期刊影响因子与单篇论文影响力的严重背离;生态学与心理学指标相关分析结果的不同折射出科学评价中自然科学、社会科学的差异。图3。表4。参考文献10。 相似文献
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近期．中国国家图书馆对外开放了针对馆藏的检索．读者通过Google Scholar（学术资源搜索）就可以检索到国家图书馆的书目数据，国家图书馆由此成为中国第一个加入Google Scholar的LibraryLink（图书馆链接）的图书馆，实现了国家图书馆数字资源门户与Google Scholar的链接。 相似文献
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利用Google Scholar统计出1995到2005年间出版的艺术类图书的被引频次,根据科学20/80定律和被引频次统计情况,确定核心书目的被引频次阈值并遴选出核心书目,其次对测定的核心书目的时间、作者、出版社、主题分布进行分析,为馆藏建设和学者选择阅读书目提供参考。 相似文献
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直接满足中文用户科研文献需求的网络搜索工具——Google Scholar初探 总被引：5，自引：0，他引：5
Google Scholar即Google学术搜索,是建立在Google搜索引擎基础上,直接面向科研需要的学术资源的网络检索工具。其搜索内容涉及诸多学科,并经业内专家评审,具有相当的权威性。该搜索引擎具有检索操作便捷化,选题标准学术化、引用搜索智能化、瞬间运行高速化等特点。Google Scholar及其中文版的出现,对于推动我国的科技进步和学术研究,具有积极意义。参考文献31。 相似文献
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介绍了Google Scholar的定义、概念、搜索技术以及它的出现给文献传递业务带来的影响和变化,论述了由Google Scholar引发的一些思考。 相似文献
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数字科研时代的引文分析-基于被引频次分析的实证研究 总被引：3，自引：0，他引：3
从期刊被引频次的角度出发,采取实证研究的方法,选择国际权威的引文数据库Web of Science和著名的搜索引擎GoogleScholar,以《美国信息科学和技术学会杂志》为文献源进行相关分析,得出在数字科研时代引文分析有必要采取多个引文分析工具,使得引文分析能跟上时代发展步伐的结论。 相似文献
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ABSTRACT Google Scholar has multiple uses as a reference tool of last resort, including citation completion, an alternative when catalogs are down, and interdisciplinary metasearching and database suggestion. During the reference desk transaction, users can be taught effective Google Scholar search techniques such as advanced search functionality and the nuances of results' groupings. In addition, reference desk interactions with Google Scholar give insight for instructional workshops. 相似文献
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Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013 to 2017 via ProQuest, with a precision of over 95%. Some ProQuest dissertations that were dual indexed with other repositories could not be retrieved with ProQuest-specific searches but could be found with Google Scholar searches of the other repositories. The Google Scholar citation counts were then compared with Mendeley reader counts, a known source of scholarly-like impact data. A fifth of the dissertations had at least one citation recorded in Google Scholar and slightly fewer had at least one Mendeley reader. Based on numerical comparisons, the Mendeley reader counts seem to be more useful for impact assessment purposes for dissertations that are less than two years old, whilst Google Scholar citations are more useful for older dissertations, especially in social sciences, arts and humanities. Google Scholar citation counts may reflect a more scholarly type of impact than that of Mendeley reader counts because dissertations attract a substantial minority of their citations from other dissertations. In summary, the new method now makes it possible for research funders, institutions and others to systematically evaluate the impact of dissertations, although additional Google Scholar queries for other online repositories are needed to ensure comprehensive coverage. 相似文献
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V. M. Moskovkin 《Scientific and Technical Information Processing》2009,36(4):198-202
This paper studies the potential of using the Google Scholar search engine for estimating the publication activities of universities
and considers a procedure for such estimation with the help of queries for the English names of universities. The publication
structures for 2008 have been built for ten selected universities of the world, including MSU. The publication activities
of the universities under consideration in 2007, has been compared based on the citation database of the US Institute for
Scientific Information (Web of Knowledge) and Google Scholar search engine (GS-publications). 相似文献
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《Journal of Web Librarianship》2013,7(2):94-108
Google Scholar is a free service that provides a simple way to broadly search for scholarly works and to connect patrons with the resources libraries provide. The researchers in this study analyzed Google Scholar usage data from 2006 for three library tools at San Francisco State University: SFX link resolver, Web Access Management proxy server, and ILLiad interlibrary loan server. Overall, the data suggested that Google Scholar had become a very useful resource in the library and was a significant addition to the library's collection of research databases. SFX data revealed requests from Google Scholar grew ten-fold from 2006 to 2011, and that Google Scholar became the top-ranked SFX source for requests in 2011. Library patrons favored Google Scholar over San Francisco State University's federated search tool, MetaLib, and it has become an important source for interlibrary loan requests. Analysis of San Francisco State University usage data will assist other libraries in their decisions about the implementation of Google Scholar. 相似文献
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《Journal of Informetrics》2007,1(1):26-34
Citation analysis was traditionally based on data from the ISI Citation indexes. Now with the appearance of Scopus, and with the free citation tool Google Scholar methods and measures are need for comparing these tools. In this paper we propose a set of measures for computing the similarity between rankings induced by ordering the retrieved publications in decreasing order of the number of citations as reported by the specific tools. The applicability of these measures is demonstrated and the results show high similarities between the rankings of the ISI Web of Science and Scopus and lower similarities between Google Scholar and the other tools. 相似文献
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Google Scholar,Web of Science,and Scopus: A systematic comparison of citations in 252 subject categories 总被引：1，自引：0，他引：1
Alberto Martín-Martín Enrique Orduna-Malea Mike Thelwall Emilio Delgado López-Cózar 《Journal of Informetrics》2018,12(4):1160-1177
Despite citation counts from Google Scholar (GS), Web of Science (WoS), and Scopus being widely consulted by researchers and sometimes used in research evaluations, there is no recent or systematic evidence about the differences between them. In response, this paper investigates 2,448,055 citations to 2299 English-language highly-cited documents from 252 GS subject categories published in 2006, comparing GS, the WoS Core Collection, and Scopus. GS consistently found the largest percentage of citations across all areas (93%–96%), far ahead of Scopus (35%–77%) and WoS (27%–73%). GS found nearly all the WoS (95%) and Scopus (92%) citations. Most citations found only by GS were from non-journal sources (48%–65%), including theses, books, conference papers, and unpublished materials. Many were non-English (19%–38%), and they tended to be much less cited than citing sources that were also in Scopus or WoS. Despite the many unique GS citing sources, Spearman correlations between citation counts in GS and WoS or Scopus are high (0.78-0.99). They are lower in the Humanities, and lower between GS and WoS than between GS and Scopus. The results suggest that in all areas GS citation data is essentially a superset of WoS and Scopus, with substantial extra coverage. 相似文献