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Neurocognitive Approach to Clustering of PubMed Query Results

机译:神经认知方法对PubMed查询结果进行聚类

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Internet literature queries return a long lists of citations, ordered according to their relevance or date. Query results may also be represented using Visual Language that takes as input a small set of semantically related concepts present in the citations. First experiments with such visualization have been done using PubMed neuronal plasticity citations with manually created semantic graphs. Here neurocognitive inspirations are used to create similar semantic graphs in an automated fashion. This way a long list of citations is changed to small semantic graphs that allow semi-automated query refinement and literature based discovery.
机译:互联网文献查询会返回一长串引文,并根据引文的相关性或日期进行排序。查询结果也可以使用可视语言表示,该可视语言将引用中出现的一小套与语义相关的概念作为输入。使用PubMed神经元可塑性引文和手动创建的语义图,已经进行了这种可视化的第一个实验。在这里,神经认知灵感被用于以自动化方式创建相似的语义图。这样,一长串的引用被更改为小的语义图,从而允许半自动查询细化和基于文献的发现。

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