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Using Force-Based Graph Layout for Clustering of Relational Data

机译:使用基于力的图布局进行关系数据聚类

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Data clustering is essential problem in database technology - successful solutions in this field provide data storing and accessing optimizations, which yield better performance characteristics. Another advantage of clustering is in relation with ability to distinguish similar data patterns and semantically interconnected entities. This in turn is very valuable for data mining and knowledge discovery activities. Although many general clustering strategies and algorithms were developed in past years, this search is still far from end, as there are many potential implementation fields, each stating its own unique requirements. This paper describes data clustering based on original spatial partitioning of force-based graph layout, which provides natural way for data organization in relational databases. Practical usage of developed approach is demonstrated.
机译:数据群集是数据库技术中的基本问题-成功的解决方案在该领域提供了数据存储和访问优化,从而产生了更好的性能特征。聚类的另一个优点是与区分相似数据模式和语义互连实体的能力有关。反过来,这对于数据挖掘和知识发现活动非常有价值。尽管在过去的几年中开发了许多通用的聚类策略和算法,但是由于存在许多潜在的实现领域,每个领域都陈述了自己的独特要求,因此这种搜索还远远没有结束。本文介绍了基于力图布局的原始空间分区的数据聚类,这为关系数据库中的数据组织提供了自然的方式。演示了开发方法的实际用法。

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