## Distributed Clustering Using Collective Principal Component Analysis (1999)

Venue: | Knowledge and Information Systems |

Citations: | 49 - 9 self |

### BibTeX

@ARTICLE{Kargupta99distributedclustering,

author = {Hillol Kargupta and Weiyun Huang and Krishnamoorthy Sivakumar and Erik Johnson},

title = {Distributed Clustering Using Collective Principal Component Analysis},

journal = {Knowledge and Information Systems},

year = {1999},

volume = {3},

pages = {2001}

}

### Years of Citing Articles

### OpenURL

### Abstract

This paper considers distributed clustering of high dimensional heterogeneous data using a distributed Principal Component Analysis (PCA) technique called the Collective PCA. It presents the Collective PCA technique that can be used independent of the clustering application. It shows a way to integrate the Collective PCA with a given o-the-shelf clustering algorithm in order to develop a distributed clustering technique. It also presents experimental results using dierent test data sets including an application for web mining.