Biclustering in data mining

被引：174

作者：

Busygin, Stanislav ^{[2
]}

Prokopyev, Oleg ^{[1
]}

Pardalos, Panos M. ^{[2
]}

机构：

[1] Univ Pittsburgh, Dept Ind Engn, Pittsburgh, PA 15261 USA

[2] Univ Florida, Dept Ind & Syst Engn, Gainesville, FL 32611 USA

来源：

COMPUTERS & OPERATIONS RESEARCH | 2008年 / 35卷 / 09期

关键词：

data mining; biclustering; classification; clustering; survey;

D O I：

10.1016/j.cor.2007.01.005

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 [计算机应用技术]; 0835 [软件工程];

摘要：

Biclustering consists in simultaneous partitioning of the set of samples and the set of their attributes (features) into subsets (classes). Samples and features classified together are supposed to have a high relevance to each other. In this paper we review the most widely used and successful biclustering techniques and their related applications. This survey is written from a theoretical viewpoint emphasizing mathematical concepts that can be met in existing biclustering techniques. (c) 2007 Published by Elsevier Ltd.

引用

页码：2964 / 2987

页数：24

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