一种无需距离函数的数据聚类方法(英文)

An approach to cluster data without distance functions

数据发掘是人工智能和数据库研究的新兴领域 ,在很多领域有着卓有成效的应用。数据聚类或分割就是其中的一种重要的数据发掘应用。传统聚类方法存在的一个问题是要求分析人员定义距离函数 ,而距离函数并不是总能获得。在本文中 。

Data mining has been recognized as a new area for artificial intelligence and database research, and found its profitable applications in many areas. Clustering or segmentation of data is an important data mining application. One of the problems with traditional clustering methods is that they require the analyst to define distance functions that are not always available. In this paper, we propose a new method for clustering without distance functions.