New models for the clustering of large databases through a hierarchical paradigm

I. L. Ruiz, G. C. García, Manuel Urbano-Cuadrado, M. Gómez-Nieto
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Abstract

The recovery of information from large databases based on similarity approach supposes a high computational cost -when the process is carried out comparing each one of the records with the search pattern. If the database records store some data structure representing the information of the problem domain by means of a graph it is possible to classify these records using a hierarchical model which considers the structural basic elements of the graphs and diminishes the computational cost of the recovery process considerably. In this paper we propose a classification model based on structural elements (cycles and chains) for large and medium databases.
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通过分层范式对大型数据库进行集群的新模型
在将每条记录与搜索模式进行比较的过程中,基于相似度方法从大型数据库中恢复信息的计算成本很高。如果数据库记录以图的形式存储了一些表示问题域信息的数据结构,则可以使用考虑图的结构基本元素的分层模型对这些记录进行分类,并大大减少恢复过程的计算成本。本文提出了一种基于结构元素(循环和链)的大中型数据库分类模型。
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