Understanding PubMed user search behavior through log analysis.
Understanding PubMed user search behavior through log analysis.
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DOI：
10.1093/database/bap018
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Lu Z
中科院分区：
文献类型：
--
作者：
Islamaj Dogan R;Murray GC;Névéol A;Lu Z
本文报告了对PubMed用户需求和行为的详细调查，以此作为改进生物医学信息检索的一步。PubMed正在为研究人员提供免费服务，他们可以从MEDLINE和生命科学期刊上获得1900多万篇生物医学文章的引文。每天有数百万用户访问它。高效的搜索工具对于生物医学研究人员跟上与他们自己的研究有关的生物医学文献至关重要。这项研究提供了对PubMed用户需求和行为的洞察。这项调查是通过分析一个月的日志数据进行的，其中包括2300多万次用户会话和5800多万次用户查询。用户与PubMed交互的多个方面通过这些日志中的证据进行了详细描述。尽管生物医学信息搜索与普通网络搜索有许多共同之处，但它也有独特的特点，这一点在这项研究中得到了明显的体现。PubMed用户在寻找信息方面更加执着，他们经常重新表述查询。最常见的三种搜索类型是按作者姓名搜索、按基因/蛋白质搜索和按疾病搜索。缩写在查询中的使用非常频繁。结果集大小等因素会影响用户的决策。对这些特征的分析在识别用户的信息需求和他们的搜索习惯方面起着至关重要的作用。反过来，这样的分析也为改进生物医学信息检索提供了有用的见解。数据库地址：http://www.ncbi.nlm.nih.gov/PubMed
This article reports on a detailed investigation of PubMed users’ needs and behavior as a step toward improving biomedical information retrieval. PubMed is providing free service to researchers with access to more than 19 million citations for biomedical articles from MEDLINE and life science journals. It is accessed by millions of users each day. Efficient search tools are crucial for biomedical researchers to keep abreast of the biomedical literature relating to their own research. This study provides insight into PubMed users’ needs and their behavior. This investigation was conducted through the analysis of one month of log data, consisting of more than 23 million user sessions and more than 58 million user queries. Multiple aspects of users’ interactions with PubMed are characterized in detail with evidence from these logs. Despite having many features in common with general Web searches, biomedical information searches have unique characteristics that are made evident in this study. PubMed users are more persistent in seeking information and they reformulate queries often. The three most frequent types of search are search by author name, search by gene/protein, and search by disease. Use of abbreviation in queries is very frequent. Factors such as result set size influence users’ decisions. Analysis of characteristics such as these plays a critical role in identifying users’ information needs and their search habits. In turn, such an analysis also provides useful insight for improving biomedical information retrieval. Database URL: http://www.ncbi.nlm.nih.gov/PubMed
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影响因子：
5.6
作者：
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通讯作者：
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影响因子：
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DOI：
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发表时间：
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期刊：
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发表时间：
2008-01-01
影响因子：
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作者：
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DOI：
10.1108/eb024320
发表时间：
1989-10-01
期刊：
ONLINE REVIEW
影响因子：
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作者：
BATES, MJ
通讯作者：
BATES, MJ