Title

SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes

Publication Type

Conference Proceeding Article

Publication Date

9-2004

Abstract

Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorithm based on CLOPE's intuitive observation about cluster histograms. Unlike CLOPE however, our algorithm is very fast and operates within the constraints of a data stream environment. In particular, we designed SCLOPE according to the recent CluStream framework. Our evaluation of SCLOPE shows very promising results. It consistently outperforms CLOPE in speed and scalability tests on our data sets while maintaining high cluster purity; it also supports cluster analysis that other algorithms in its class do not.

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

Data Warehousing and Knowledge Discovery: Proceedings of the 6th International Conference (DaWaK 2004)

Volume

3181

First Page

209

Last Page

218

ISBN

9783540300762

Identifier

10.1007/978-3-540-30076-2_21

Publisher

Springer Verlag

City or Country

Zaragoza, Spain

Additional URL

http://dx.doi.org/10.1007/978-3-540-30076-2_21