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MINING SCIENTIFIC RESULTS THROUGH THE COMBINED USE OF CLUSTERING AND LINEAR PROGRAMMING TECHNIQUES

机译:通过联合使用聚类和线性规划技术来挖掘科学结果

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The paper proposes a technique based on a combined approach of data mining algorithms and linear programming methods for classifying organizational units, such as research centers. We exploit clustering algorithms for grouping information concerning the scientific activity of research centers. We also show that the replacement of an expensive efficiency measurement, based on the solution of linear programs, with a simple formula allows clusters of very good quality to be computed efficiently. Some initial experimental results, obtained from an analysis of research centers in the agro-food sector, show the effectiveness of our approach, both from an efficiency and a quality-of-results point of view.
机译:本文提出了一种基于数据挖掘算法的组合方法和用于分类组织单位的线性规划方法的技术,例如研究中心。我们利用集群算法进行分组信息,了解研究中心的科学活动。我们还表明,根据线性程序的解决方案,更换昂贵的效率测量,简单的公式允许有效地计算非常好的质量的集群。一些初步的实验结果,从农业食品部门的研究中心分析中获得,既可从效率和结果质量方面表明我们的方法的有效性。

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