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A New Scheme to Visualize Clusters Model in Data Mining

机译:一种可视化数据挖掘中集群模型的新方案

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This paper presents the design and implementation of a new scheme to visualize clusters model called IVCM, in the context of a data-mining process. The visualization of a cluster model becomes complex when the dataset is high volume, density and dimensionality. The design of IVCM scheme is based on four characteristics: interactive visualization, combination of models, ad-hoc graphics artifacts, and use metrics. The objective of this scheme is to contribute to the analysis and understanding of a clustering model. Metrics considered in this proposed scheme, allow comparison instances of different clusters, which in turn helps to understand how groups are composed. Through the implementation of a web visual environment that meets the characteristics defined in IVCM, and an online assessment of 23 users, positive results on the usefulness of this new visualization scheme are achieved.
机译:本文介绍了在数据挖掘过程的上下文中对称为IVCM称为IVCM的集群模型的新方案的设计和实现。当数据集是高容量,密度和维度时,集群模型的可视化变得复杂。 IVCM方案的设计基于四个特征:交互式可视化,模型组合,ad-hoc图形工件,以及使用度量。该方案的目的是有助于分析和理解聚类模型。在此提出的方案中考虑的指标允许不同群集的比较实例,这反过来有助于了解群体的组成。通过实现符合IVCM中定义的特征的网络视觉环境,实现了23个用户的在线评估,实现了对这种新可视化方案的有用性的积极结果。

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