A new shifting grid clustering algorithm

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

72 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)503-514
Journal / PublicationPattern Recognition
Volume37
Issue number3
Publication statusPublished - Mar 2004

Abstract

A new density- and grid-based type clustering algorithm using the concept of shifting grid is proposed. The proposed algorithm is a non-parametric type, which does not require users inputting parameters. It divides each dimension of the data space into certain intervals to form a grid structure in the data space. Based on the concept of sliding window, shifting of the whole grid structure is introduced to obtain a more descriptive density profile. As a result, we are able to enhance the accuracy of the results. Compared with many conventional algorithms, this algorithm is computational efficient because it clusters data in a way of cell rather than in points. © 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Research Area(s)

  • Clustering, Shifting grid

Citation Format(s)

A new shifting grid clustering algorithm. / Ma, Eden W.M.; Chow, Tommy W.S.
In: Pattern Recognition, Vol. 37, No. 3, 03.2004, p. 503-514.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review