A human-computer interactive method for projected clustering
A human-computer interactive method for projected clustering
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DOI：
10.1109/tkde.2004.1269669
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发表时间：
2004-04
影响因子：
8.9
通讯作者：
C. Aggarwal
中科院分区：
文献类型：
--
作者：
C. Aggarwal
聚类是数据挖掘应用程序（如客户细分）的中心任务。高维数据由于其固有的稀疏性一直是聚类算法的一个挑战。因此，最近提出了在数据的隐藏子空间中找到聚类的技术。然而，由于数据的行为在不同的子空间中可能会有很大的不同，因此通常很难使用简单的数学形式来定义集群的概念。将聚类视为优化任意选择的目标函数的精确问题的广泛使用的实践通常会导致误导性的结果。事实上，正确的聚类定义不仅会随应用程序和数据集而变化，还会随最终用户的感知而变化。这使得很难将聚类问题的定义与最终用户的感知分开。我们提出了一个系统，它执行高维聚类之间的合作，人类和计算机。集群创建的复杂任务是通过人类直觉和计算机提供的计算支持相结合来完成的。其结果是一个系统，它利用人类和计算机的最佳能力来解决聚类问题。
Clustering is a central task in data mining applications such as customer segmentation. High-dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Therefore, techniques have recently been proposed to find clusters in hidden subspaces of the data. However, since the behavior of the data can vary considerably in different subspaces, it is often difficult to define the notion of a cluster with the use of simple mathematical formalizations. The widely used practice of treating clustering as the exact problem of optimizing an arbitrarily chosen objective function can often lead to misleading results. In fact, the proper clustering definition may vary not only with the application and data set but also with the perceptions of the end user. This makes it difficult to separate the definition of the clustering problem from the perception of an end-user. We propose a system, which performs high-dimensional clustering by cooperation between the human and the computer. The complex task of cluster creation is accomplished through a combination of human intuition and the computational support provided by the computer. The result is a system, which leverages the best abilities of both the human and the computer for solving the clustering problem.