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Time aware knowledge extraction to analyze nanosafety cluster scientific activities

机译:具有时间意识的知识提取以分析纳米安全集群的科学活动

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With the rapid development ot biomedical sciences, a growing amount of papers reporting new scientific findings are published and indexed in different unstructured biomedical data sources. In order to really appreciate and effectively benefit from the availability of this amount of data there is an urgent need to support the deployment of intelligent information services, such as: temporal trends and group detection, expert finding, review experts, link prediction, and so on. This need is even more stressed if we analyze dissemination activity of emerging scientific communities that are working on specific research topics in the field of biomedical science. Motivated by the fact that nanotechnologies are one of the key enabling technologies nowadays, in this paper we instantiate and contextualize the Time Aware Knowledge Extraction (TAKE) methodology, introduced in previous work, as a tool to analyze the activities of the nano-safety scientific community coordinated by the EU NanoSafety Cluster (NSC). This methodology enables us to extract timed association rules. To validate and give evidence of the goodness of these rules, a summary of the so obtained results of the analysis is provided identifying distinguishing features, and detecting emerging collaboration among the NSC's Working Groups and their members over the timeline.
机译:随着生物医学科学的飞速发展,越来越多的报告新科学发现的论文在不同的非结构化生物医学数据源中发表和索引。为了真正地欣赏并有效地从如此大量的数据中受益,迫切需要支持智能信息服务的部署,例如:时间趋势和组检测,专家发现,审阅专家,链接预测等。在。如果我们分析正在研究生物医学领域特定研究主题的新兴科学界的传播活动,则这一需求将更加受到强调。受纳米技术是当今关键的使能技术之一这一事实的激励,在本文中,我们将先前工作中介绍的时间感知知识提取(TAKE)方法实例化并进行上下文化,以作为分析纳米安全科学活动的工具。由欧盟纳米安全小组(NSC)协调的社区。这种方法使我们能够提取定时关联规则。为了验证这些规则的有效性并提供证据,提供了如此获得的分析结果的摘要,以识别不同的特征,并在时间轴上检测NSC工作组及其成员之间正在出现的协作。

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