A study of density-grid based clustering algorithms on data streams

Amini, A. and Saybani, M.R. and Sahaf Yazdi, S.R.A. (2011) A study of density-grid based clustering algorithms on data streams. In: 2011 Eight International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 26-28 July 2011, Shanghai, China.

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Clustering data streams attracted many researchers since the aPlications that generate data streams have become more popular. Several clustering algorithms have been introduced for data streams based on distance which are incompetent to find cluster of arbitrary shapes and cannot handle the outliers. Density-based clustering algorithms are remarkable not only to find arbitrarily shaped clusters but also to deal with noise in data. In density-based clustering algorithms, dense areas of objects in the data space are considered as clusters which are segregated by low-density area. Another group of the clustering methods for data streams is grid-based clustering where the data space is quantized into finite number of cells which form the grid structure and perform clustering on the grids. Grid-based clustering maps the infinite number of data records in data stream to finite numbers of grids. In this paper we review the grid based clustering algorithms that use density-based algorithms or density concept for the clustering. We called them density-grid clustering algorithms. We explore the algorithms in details and the merits and limitations of them. The algorithms are also summarized in a table based on the important features. Besides that, we discuss about how well the algorithms address the challenging issues in the clustering data streams.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Data streams, Density-based clustering, Grid-based clustering, Density-grid clustering
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Computer Science & Information Technology > Department of Information Science
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 07 Apr 2015 23:41
Last Modified: 07 Apr 2015 23:41
URI: http://eprints.um.edu.my/id/eprint/13232

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