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Understanding PubMed? user search behavior through log analysis

机译：了解PubMed？通过日志分析的用户搜索行为

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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
机译：本文报告了对PubMed用户的需求和行为的详细调查，以此作为改善生物医学信息检索的步骤。 PubMed正在为研究人员提供免费服务，可以从MEDLINE和生命科学期刊获得超过1900万次引用的生物医学文章。每天都有数百万的用户访问它。高效的搜索工具对于生物医学研究人员保持与自身研究有关的生物医学文献至关重要。这项研究可深入了解PubMed用户的需求及其行为。这项调查是通过分析一个月的日志数据进行的，该日志数据包含2300万用户会话和5800万用户查询。这些日志中的证据详细描述了用户与PubMed交互的多个方面。尽管具有与常规Web搜索相同的许多功能，但生物医学信息搜索仍具有独特的特征，这一点在本研究中显而易见。 PubMed用户在查找信息方面更加执着，并且经常重新制定查询条件。三种最常见的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。查询中经常使用缩写。结果集大小等因素会影响用户的决策。诸如此类的特征分析在识别用户的信息需求及其搜索习惯中起着至关重要的作用。反过来，这种分析也为改善生物医学信息检索提供了有用的见识。数据库网址：http://www.ncbi.nlm.nih.gov/PubMed

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