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How user intelligence is improving PubMed
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AI
DOI：10.1038/nbt.4267.png)
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摘要
En 中文
PubMed is a widely used search engine for biomedical literature. It is developed and maintained by the US National Library of Medicine/National Center for Biotechnology Information and is visited daily by millions of users around the world. For decades, PubMed has used advanced artificial intelligence technologies that extract patterns of collective user activity, such as machine learning and natural language processing, to inform the algorithmic changes that ultimately improve a user's search experience. Although these efforts have led to objective improvements in search quality, the technical underpinnings remain largely invisible and go largely unnoticed by most users. Here we describe how these 'under-the-hood' techniques work within PubMed and report how their effectiveness and usage is assessed in real-world scenarios. In doing so, we hope to increase the transparency of the PubMed system and enable users to make more effective use of the search engine. We also identify open challenges and new opportunities for computational researchers to explore the potential of future improvements.
Keyword:
INFORMATION-RETRIEVAL
STRATEGIES
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
41.7
论文数:
1.2W
被引数:
10.1W
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