Subspace clustering

被引：50

作者：

Kriegel, Hans-Peter ^{[1
]}

Kroeger, Peer ^{[1
]}

Zimek, Arthur ^{[1
]}

机构：

[1] Univ Munich, Inst Informat, D-80538 Munich M, Germany

来源：

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY | 2012年 / 2卷 / 04期

关键词：

HIGH-DIMENSIONAL DATA; ALGORITHM; SELECTION; VARIABLES;

D O I：

10.1002/widm.1057

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Subspace clustering refers to the task of identifying clusters of similar objects or data records (vectors) where the similarity is defined with respect to a subset of the attributes (i.e., a subspace of the data space). The subspace is not necessarily (and actually is usually not) the same for different clusters within one clustering solution. In this article, the problems motivating subspace clustering are sketched, different definitions and usages of subspaces for clustering are described, and exemplary algorithmic solutions are discussed. Finally, we sketch current research directions. (c) 2012 Wiley Periodicals, Inc.

引用

页码：351 / 364

页数：14